Zipf0 New Model Test Data Result Combined

Result

Model Summaries

Model Better than base % of the times
LR_10[cache_size=0.001,treshold=0.3] 0
LR_10[cache_size=0.001,treshold=0.5] 0
LR_10[cache_size=0.001,treshold=0.6] 0
LR_10[cache_size=0.001,treshold=0.7] 0
LR_10[cache_size=0.001,treshold=0.8] 0
LR_10[cache_size=0.001,treshold=0.9] 0
LR_10[cache_size=All,treshold=0.3] 60
LR_10[cache_size=All,treshold=0.5] 52
LR_10[cache_size=All,treshold=0.6] 32
LR_10[cache_size=All,treshold=0.7] 32
LR_10[cache_size=All,treshold=0.8] 28
LR_10[cache_size=All,treshold=0.9] 4
LR_11[cache_size=0.001,treshold=0.3] 0
LR_11[cache_size=0.001,treshold=0.5] 0
LR_11[cache_size=0.001,treshold=0.6] 0
LR_11[cache_size=0.001,treshold=0.7] 0
LR_11[cache_size=0.001,treshold=0.8] 0
LR_11[cache_size=0.001,treshold=0.9] 0
LR_11[cache_size=All,treshold=0.3] 60
LR_11[cache_size=All,treshold=0.5] 48
LR_11[cache_size=All,treshold=0.6] 32
LR_11[cache_size=All,treshold=0.7] 36
LR_11[cache_size=All,treshold=0.8] 28
LR_11[cache_size=All,treshold=0.9] 4
LR_12[cache_size=0.001,treshold=0.3] 0
LR_12[cache_size=0.001,treshold=0.5] 0
LR_12[cache_size=0.001,treshold=0.6] 0
LR_12[cache_size=0.001,treshold=0.7] 0
LR_12[cache_size=0.001,treshold=0.8] 0
LR_12[cache_size=0.001,treshold=0.9] 0
LR_12[cache_size=All,treshold=0.3] 64
LR_12[cache_size=All,treshold=0.5] 48
LR_12[cache_size=All,treshold=0.6] 32
LR_12[cache_size=All,treshold=0.7] 36
LR_12[cache_size=All,treshold=0.8] 32
LR_12[cache_size=All,treshold=0.9] 4
LR_13[cache_size=0.001,treshold=0.3] 0
LR_13[cache_size=0.001,treshold=0.5] 0
LR_13[cache_size=0.001,treshold=0.6] 0
LR_13[cache_size=0.001,treshold=0.7] 0
LR_13[cache_size=0.001,treshold=0.8] 0
LR_13[cache_size=0.001,treshold=0.9] 0
LR_13[cache_size=All,treshold=0.3] 60
LR_13[cache_size=All,treshold=0.5] 28
LR_13[cache_size=All,treshold=0.6] 16
LR_13[cache_size=All,treshold=0.7] 0
LR_13[cache_size=All,treshold=0.8] 0
LR_13[cache_size=All,treshold=0.9] 0
LR_14[cache_size=0.001,treshold=0.3] 0
LR_14[cache_size=0.001,treshold=0.5] 0
LR_14[cache_size=0.001,treshold=0.6] 0
LR_14[cache_size=0.001,treshold=0.7] 0
LR_14[cache_size=0.001,treshold=0.8] 0
LR_14[cache_size=0.001,treshold=0.9] 0
LR_14[cache_size=All,treshold=0.3] 60
LR_14[cache_size=All,treshold=0.5] 28
LR_14[cache_size=All,treshold=0.6] 16
LR_14[cache_size=All,treshold=0.7] 0
LR_14[cache_size=All,treshold=0.8] 0
LR_14[cache_size=All,treshold=0.9] 0
LR_15[cache_size=0.001,treshold=0.3] 0
LR_15[cache_size=0.001,treshold=0.5] 0
LR_15[cache_size=0.001,treshold=0.6] 0
LR_15[cache_size=0.001,treshold=0.7] 0
LR_15[cache_size=0.001,treshold=0.8] 0
LR_15[cache_size=0.001,treshold=0.9] 0
LR_15[cache_size=All,treshold=0.3] 60
LR_15[cache_size=All,treshold=0.5] 28
LR_15[cache_size=All,treshold=0.6] 16
LR_15[cache_size=All,treshold=0.7] 0
LR_15[cache_size=All,treshold=0.8] 0
LR_15[cache_size=All,treshold=0.9] 0
LR_7[cache_size=0.001,treshold=0.3] 0
LR_7[cache_size=0.001,treshold=0.5] 0
LR_7[cache_size=0.001,treshold=0.6] 0
LR_7[cache_size=0.001,treshold=0.7] 0
LR_7[cache_size=0.001,treshold=0.8] 0
LR_7[cache_size=0.001,treshold=0.9] 0
LR_7[cache_size=All,treshold=0.3] 60
LR_7[cache_size=All,treshold=0.5] 52
LR_7[cache_size=All,treshold=0.6] 48
LR_7[cache_size=All,treshold=0.7] 36
LR_7[cache_size=All,treshold=0.8] 44
LR_7[cache_size=All,treshold=0.9] 16
LR_8[cache_size=0.001,treshold=0.3] 0
LR_8[cache_size=0.001,treshold=0.5] 0
LR_8[cache_size=0.001,treshold=0.6] 0
LR_8[cache_size=0.001,treshold=0.7] 0
LR_8[cache_size=0.001,treshold=0.8] 0
LR_8[cache_size=0.001,treshold=0.9] 0
LR_8[cache_size=All,treshold=0.3] 60
LR_8[cache_size=All,treshold=0.5] 52
LR_8[cache_size=All,treshold=0.6] 36
LR_8[cache_size=All,treshold=0.7] 36
LR_8[cache_size=All,treshold=0.8] 40
LR_8[cache_size=All,treshold=0.9] 12
LR_9[cache_size=0.001,treshold=0.3] 0
LR_9[cache_size=0.001,treshold=0.5] 0
LR_9[cache_size=0.001,treshold=0.6] 0
LR_9[cache_size=0.001,treshold=0.7] 0
LR_9[cache_size=0.001,treshold=0.8] 0
LR_9[cache_size=0.001,treshold=0.9] 0
LR_9[cache_size=All,treshold=0.3] 60
LR_9[cache_size=All,treshold=0.5] 52
LR_9[cache_size=All,treshold=0.6] 44
LR_9[cache_size=All,treshold=0.7] 36
LR_9[cache_size=All,treshold=0.8] 40
LR_9[cache_size=All,treshold=0.9] 16
LR_10[cache_size=0.01,treshold=0.3] 80
LR_10[cache_size=0.01,treshold=0.5] 80
LR_10[cache_size=0.01,treshold=0.6] 80
LR_10[cache_size=0.01,treshold=0.7] 0
LR_10[cache_size=0.01,treshold=0.8] 0
LR_10[cache_size=0.01,treshold=0.9] 0
LR_11[cache_size=0.01,treshold=0.3] 80
LR_11[cache_size=0.01,treshold=0.5] 60
LR_11[cache_size=0.01,treshold=0.6] 60
LR_11[cache_size=0.01,treshold=0.7] 40
LR_11[cache_size=0.01,treshold=0.8] 0
LR_11[cache_size=0.01,treshold=0.9] 0
LR_12[cache_size=0.01,treshold=0.3] 80
LR_12[cache_size=0.01,treshold=0.5] 60
LR_12[cache_size=0.01,treshold=0.6] 60
LR_12[cache_size=0.01,treshold=0.7] 40
LR_12[cache_size=0.01,treshold=0.8] 0
LR_12[cache_size=0.01,treshold=0.9] 0
LR_13[cache_size=0.01,treshold=0.3] 80
LR_13[cache_size=0.01,treshold=0.5] 80
LR_13[cache_size=0.01,treshold=0.6] 80
LR_13[cache_size=0.01,treshold=0.7] 0
LR_13[cache_size=0.01,treshold=0.8] 0
LR_13[cache_size=0.01,treshold=0.9] 0
LR_14[cache_size=0.01,treshold=0.3] 80
LR_14[cache_size=0.01,treshold=0.5] 60
LR_14[cache_size=0.01,treshold=0.6] 60
LR_14[cache_size=0.01,treshold=0.7] 80
LR_14[cache_size=0.01,treshold=0.8] 0
LR_14[cache_size=0.01,treshold=0.9] 0
LR_15[cache_size=0.01,treshold=0.3] 80
LR_15[cache_size=0.01,treshold=0.5] 60
LR_15[cache_size=0.01,treshold=0.6] 60
LR_15[cache_size=0.01,treshold=0.7] 80
LR_15[cache_size=0.01,treshold=0.8] 0
LR_15[cache_size=0.01,treshold=0.9] 0
LR_7[cache_size=0.01,treshold=0.3] 80
LR_7[cache_size=0.01,treshold=0.5] 80
LR_7[cache_size=0.01,treshold=0.6] 80
LR_7[cache_size=0.01,treshold=0.7] 0
LR_7[cache_size=0.01,treshold=0.8] 0
LR_7[cache_size=0.01,treshold=0.9] 0
LR_8[cache_size=0.01,treshold=0.3] 80
LR_8[cache_size=0.01,treshold=0.5] 80
LR_8[cache_size=0.01,treshold=0.6] 60
LR_8[cache_size=0.01,treshold=0.7] 60
LR_8[cache_size=0.01,treshold=0.8] 0
LR_8[cache_size=0.01,treshold=0.9] 0
LR_9[cache_size=0.01,treshold=0.3] 80
LR_9[cache_size=0.01,treshold=0.5] 80
LR_9[cache_size=0.01,treshold=0.6] 80
LR_9[cache_size=0.01,treshold=0.7] 60
LR_9[cache_size=0.01,treshold=0.8] 0
LR_9[cache_size=0.01,treshold=0.9] 0
LR_10[cache_size=0.1,treshold=0.3] 80
LR_10[cache_size=0.1,treshold=0.5] 60
LR_10[cache_size=0.1,treshold=0.6] 60
LR_10[cache_size=0.1,treshold=0.7] 60
LR_10[cache_size=0.1,treshold=0.8] 40
LR_10[cache_size=0.1,treshold=0.9] 20
LR_11[cache_size=0.1,treshold=0.3] 80
LR_11[cache_size=0.1,treshold=0.5] 60
LR_11[cache_size=0.1,treshold=0.6] 60
LR_11[cache_size=0.1,treshold=0.7] 60
LR_11[cache_size=0.1,treshold=0.8] 40
LR_11[cache_size=0.1,treshold=0.9] 20
LR_12[cache_size=0.1,treshold=0.3] 80
LR_12[cache_size=0.1,treshold=0.5] 60
LR_12[cache_size=0.1,treshold=0.6] 40
LR_12[cache_size=0.1,treshold=0.7] 40
LR_12[cache_size=0.1,treshold=0.8] 20
LR_12[cache_size=0.1,treshold=0.9] 20
LR_13[cache_size=0.1,treshold=0.3] 80
LR_13[cache_size=0.1,treshold=0.5] 60
LR_13[cache_size=0.1,treshold=0.6] 80
LR_13[cache_size=0.1,treshold=0.7] 40
LR_13[cache_size=0.1,treshold=0.8] 0
LR_13[cache_size=0.1,treshold=0.9] 0
LR_14[cache_size=0.1,treshold=0.3] 80
LR_14[cache_size=0.1,treshold=0.5] 60
LR_14[cache_size=0.1,treshold=0.6] 60
LR_14[cache_size=0.1,treshold=0.7] 60
LR_14[cache_size=0.1,treshold=0.8] 0
LR_14[cache_size=0.1,treshold=0.9] 0
LR_15[cache_size=0.1,treshold=0.3] 80
LR_15[cache_size=0.1,treshold=0.5] 60
LR_15[cache_size=0.1,treshold=0.6] 60
LR_15[cache_size=0.1,treshold=0.7] 60
LR_15[cache_size=0.1,treshold=0.8] 0
LR_15[cache_size=0.1,treshold=0.9] 0
LR_7[cache_size=0.1,treshold=0.3] 80
LR_7[cache_size=0.1,treshold=0.5] 80
LR_7[cache_size=0.1,treshold=0.6] 40
LR_7[cache_size=0.1,treshold=0.7] 60
LR_7[cache_size=0.1,treshold=0.8] 0
LR_7[cache_size=0.1,treshold=0.9] 0
LR_8[cache_size=0.1,treshold=0.3] 80
LR_8[cache_size=0.1,treshold=0.5] 80
LR_8[cache_size=0.1,treshold=0.6] 80
LR_8[cache_size=0.1,treshold=0.7] 60
LR_8[cache_size=0.1,treshold=0.8] 0
LR_8[cache_size=0.1,treshold=0.9] 0
LR_9[cache_size=0.1,treshold=0.3] 80
LR_9[cache_size=0.1,treshold=0.5] 80
LR_9[cache_size=0.1,treshold=0.6] 80
LR_9[cache_size=0.1,treshold=0.7] 40
LR_9[cache_size=0.1,treshold=0.8] 0
LR_9[cache_size=0.1,treshold=0.9] 0
LR_10[cache_size=0.2,treshold=0.3] 40
LR_10[cache_size=0.2,treshold=0.5] 60
LR_10[cache_size=0.2,treshold=0.6] 60
LR_10[cache_size=0.2,treshold=0.7] 60
LR_10[cache_size=0.2,treshold=0.8] 0
LR_10[cache_size=0.2,treshold=0.9] 0
LR_11[cache_size=0.2,treshold=0.3] 40
LR_11[cache_size=0.2,treshold=0.5] 60
LR_11[cache_size=0.2,treshold=0.6] 60
LR_11[cache_size=0.2,treshold=0.7] 60
LR_11[cache_size=0.2,treshold=0.8] 0
LR_11[cache_size=0.2,treshold=0.9] 0
LR_12[cache_size=0.2,treshold=0.3] 40
LR_12[cache_size=0.2,treshold=0.5] 60
LR_12[cache_size=0.2,treshold=0.6] 60
LR_12[cache_size=0.2,treshold=0.7] 60
LR_12[cache_size=0.2,treshold=0.8] 0
LR_12[cache_size=0.2,treshold=0.9] 0
LR_13[cache_size=0.2,treshold=0.3] 40
LR_13[cache_size=0.2,treshold=0.5] 40
LR_13[cache_size=0.2,treshold=0.6] 40
LR_13[cache_size=0.2,treshold=0.7] 60
LR_13[cache_size=0.2,treshold=0.8] 0
LR_13[cache_size=0.2,treshold=0.9] 0
LR_14[cache_size=0.2,treshold=0.3] 40
LR_14[cache_size=0.2,treshold=0.5] 40
LR_14[cache_size=0.2,treshold=0.6] 40
LR_14[cache_size=0.2,treshold=0.7] 60
LR_14[cache_size=0.2,treshold=0.8] 0
LR_14[cache_size=0.2,treshold=0.9] 0
LR_15[cache_size=0.2,treshold=0.3] 60
LR_15[cache_size=0.2,treshold=0.5] 40
LR_15[cache_size=0.2,treshold=0.6] 40
LR_15[cache_size=0.2,treshold=0.7] 40
LR_15[cache_size=0.2,treshold=0.8] 0
LR_15[cache_size=0.2,treshold=0.9] 0
LR_7[cache_size=0.2,treshold=0.3] 40
LR_7[cache_size=0.2,treshold=0.5] 40
LR_7[cache_size=0.2,treshold=0.6] 60
LR_7[cache_size=0.2,treshold=0.7] 60
LR_7[cache_size=0.2,treshold=0.8] 0
LR_7[cache_size=0.2,treshold=0.9] 0
LR_8[cache_size=0.2,treshold=0.3] 60
LR_8[cache_size=0.2,treshold=0.5] 40
LR_8[cache_size=0.2,treshold=0.6] 60
LR_8[cache_size=0.2,treshold=0.7] 60
LR_8[cache_size=0.2,treshold=0.8] 0
LR_8[cache_size=0.2,treshold=0.9] 0
LR_9[cache_size=0.2,treshold=0.3] 60
LR_9[cache_size=0.2,treshold=0.5] 40
LR_9[cache_size=0.2,treshold=0.6] 60
LR_9[cache_size=0.2,treshold=0.7] 60
LR_9[cache_size=0.2,treshold=0.8] 0
LR_9[cache_size=0.2,treshold=0.9] 0
LR_10[cache_size=0.4,treshold=0.3] 60
LR_10[cache_size=0.4,treshold=0.5] 80
LR_10[cache_size=0.4,treshold=0.6] 80
LR_10[cache_size=0.4,treshold=0.7] 40
LR_10[cache_size=0.4,treshold=0.8] 40
LR_10[cache_size=0.4,treshold=0.9] 20
LR_11[cache_size=0.4,treshold=0.3] 60
LR_11[cache_size=0.4,treshold=0.5] 80
LR_11[cache_size=0.4,treshold=0.6] 60
LR_11[cache_size=0.4,treshold=0.7] 40
LR_11[cache_size=0.4,treshold=0.8] 0
LR_11[cache_size=0.4,treshold=0.9] 0
LR_12[cache_size=0.4,treshold=0.3] 80
LR_12[cache_size=0.4,treshold=0.5] 80
LR_12[cache_size=0.4,treshold=0.6] 80
LR_12[cache_size=0.4,treshold=0.7] 40
LR_12[cache_size=0.4,treshold=0.8] 0
LR_12[cache_size=0.4,treshold=0.9] 0
LR_13[cache_size=0.4,treshold=0.3] 60
LR_13[cache_size=0.4,treshold=0.5] 80
LR_13[cache_size=0.4,treshold=0.6] 80
LR_13[cache_size=0.4,treshold=0.7] 40
LR_13[cache_size=0.4,treshold=0.8] 20
LR_13[cache_size=0.4,treshold=0.9] 20
LR_14[cache_size=0.4,treshold=0.3] 60
LR_14[cache_size=0.4,treshold=0.5] 80
LR_14[cache_size=0.4,treshold=0.6] 80
LR_14[cache_size=0.4,treshold=0.7] 40
LR_14[cache_size=0.4,treshold=0.8] 20
LR_14[cache_size=0.4,treshold=0.9] 20
LR_15[cache_size=0.4,treshold=0.3] 80
LR_15[cache_size=0.4,treshold=0.5] 80
LR_15[cache_size=0.4,treshold=0.6] 80
LR_15[cache_size=0.4,treshold=0.7] 40
LR_15[cache_size=0.4,treshold=0.8] 20
LR_15[cache_size=0.4,treshold=0.9] 20
LR_7[cache_size=0.4,treshold=0.3] 80
LR_7[cache_size=0.4,treshold=0.5] 80
LR_7[cache_size=0.4,treshold=0.6] 80
LR_7[cache_size=0.4,treshold=0.7] 40
LR_7[cache_size=0.4,treshold=0.8] 20
LR_7[cache_size=0.4,treshold=0.9] 40
LR_8[cache_size=0.4,treshold=0.3] 80
LR_8[cache_size=0.4,treshold=0.5] 80
LR_8[cache_size=0.4,treshold=0.6] 80
LR_8[cache_size=0.4,treshold=0.7] 20
LR_8[cache_size=0.4,treshold=0.8] 0
LR_8[cache_size=0.4,treshold=0.9] 0
LR_9[cache_size=0.4,treshold=0.3] 80
LR_9[cache_size=0.4,treshold=0.5] 80
LR_9[cache_size=0.4,treshold=0.6] 80
LR_9[cache_size=0.4,treshold=0.7] 20
LR_9[cache_size=0.4,treshold=0.8] 0
LR_9[cache_size=0.4,treshold=0.9] 0
Offline Clock 1st iteration 0
Offline Clock 2nd iteration 100
Zipf Optimal Distribution 56

Promotion Reduced (%)

Model Max Min Avg Mdn
LR_10[cache_size=0.001,treshold=0.3] 97.5251 97.4386 97.476 97.4733
LR_10[cache_size=0.001,treshold=0.5] 93.7553 93.6115 93.6695 93.6449
LR_10[cache_size=0.001,treshold=0.6] 87.3734 87.1943 87.2682 87.2438
LR_10[cache_size=0.001,treshold=0.7] 26.0166 25.6524 25.8338 25.8229
LR_10[cache_size=0.001,treshold=0.8] 1.66789 1.61523 1.6328 1.62872
LR_10[cache_size=0.001,treshold=0.9] 0 0 0 0
LR_10[cache_size=All,treshold=0.3] 98.0623 90.7947 95.1189 95.4773
LR_10[cache_size=All,treshold=0.5] 86.4887 13.4401 46.6968 52.599
LR_10[cache_size=All,treshold=0.6] 76.5894 0.700736 28.9161 16.4192
LR_10[cache_size=All,treshold=0.7] 58.9215 0.223497 15.3703 6.63903
LR_10[cache_size=All,treshold=0.8] 18.1337 0.0247083 5.37182 4.12296
LR_10[cache_size=All,treshold=0.9] 3.45624 0.00273211 1.52489 1.60022
LR_11[cache_size=0.001,treshold=0.3] 91.9068 91.6789 91.737 91.6959
LR_11[cache_size=0.001,treshold=0.5] 75.224 75.0761 75.1469 75.1551
LR_11[cache_size=0.001,treshold=0.6] 58.7067 58.5526 58.6333 58.6431
LR_11[cache_size=0.001,treshold=0.7] 26.8304 26.4186 26.6328 26.6834
LR_11[cache_size=0.001,treshold=0.8] 0.0351018 0.0159226 0.0242171 0.0229968
LR_11[cache_size=0.001,treshold=0.9] 0 0 0 0
LR_11[cache_size=All,treshold=0.3] 98.119 70.9173 90.6142 94.2833
LR_11[cache_size=All,treshold=0.5] 85.2065 14.0347 41.6486 28.5799
LR_11[cache_size=All,treshold=0.6] 76.3445 0.726802 26.714 9.63783
LR_11[cache_size=All,treshold=0.7] 59.9017 0.241822 14.6793 3.7238
LR_11[cache_size=All,treshold=0.8] 23.2517 0.0280467 5.98543 2.12261
LR_11[cache_size=All,treshold=0.9] 3.5706 0.00303224 1.38632 0.809615
LR_12[cache_size=0.001,treshold=0.3] 96.3863 96.2251 96.285 96.2771
LR_12[cache_size=0.001,treshold=0.5] 85.2348 85.0491 85.1357 85.1452
LR_12[cache_size=0.001,treshold=0.6] 71.7157 71.628 71.6869 71.6919
LR_12[cache_size=0.001,treshold=0.7] 43.0577 42.8483 42.9785 42.9977
LR_12[cache_size=0.001,treshold=0.8] 0 0 0 0
LR_12[cache_size=0.001,treshold=0.9] 0 0 0 0
LR_12[cache_size=All,treshold=0.3] 98.1894 58.5912 87.9937 93.9287
LR_12[cache_size=All,treshold=0.5] 84.2409 14.4434 39.4358 18.1608
LR_12[cache_size=All,treshold=0.6] 75.5171 0.732406 26.1776 9.67854
LR_12[cache_size=All,treshold=0.7] 59.6489 0.244398 14.1821 2.88019
LR_12[cache_size=All,treshold=0.8] 22.6008 0.0280312 5.76445 1.64825
LR_12[cache_size=All,treshold=0.9] 3.53358 0.00298583 1.32528 0.557424
LR_13[cache_size=0.001,treshold=0.3] 97.5371 97.4516 97.4848 97.4754
LR_13[cache_size=0.001,treshold=0.5] 93.7102 93.5653 93.6261 93.6148
LR_13[cache_size=0.001,treshold=0.6] 87.3296 87.1502 87.2206 87.1728
LR_13[cache_size=0.001,treshold=0.7] 26.0862 25.7144 25.8855 25.879
LR_13[cache_size=0.001,treshold=0.8] 1.646 1.56919 1.60719 1.60666
LR_13[cache_size=0.001,treshold=0.9] 0 0 0 0
LR_13[cache_size=All,treshold=0.3] 98.4936 81.7862 90.8247 92.2814
LR_13[cache_size=All,treshold=0.5] 76.5658 0.0120017 25.3015 4.51844
LR_13[cache_size=All,treshold=0.6] 42.0709 0.00108558 8.72344 0.470934
LR_13[cache_size=All,treshold=0.7] 1.00954 -5.53978e-06 0.221484 2.10371e-05
LR_13[cache_size=All,treshold=0.8] 0.995569 0 0.216238 0
LR_13[cache_size=All,treshold=0.9] 0.986525 0 0.214378 0
LR_14[cache_size=0.001,treshold=0.3] 91.9068 91.6789 91.737 91.6959
LR_14[cache_size=0.001,treshold=0.5] 75.224 75.0761 75.1469 75.1551
LR_14[cache_size=0.001,treshold=0.6] 58.7067 58.5526 58.6331 58.6431
LR_14[cache_size=0.001,treshold=0.7] 27.3288 26.9986 27.1804 27.238
LR_14[cache_size=0.001,treshold=0.8] 0.0280814 0.011942 0.0174121 0.0159978
LR_14[cache_size=0.001,treshold=0.9] 0 0 0 0
LR_14[cache_size=All,treshold=0.3] 98.5848 67.9597 87.5698 92.7413
LR_14[cache_size=All,treshold=0.5] 76.5447 0.014624 25.5286 6.62513
LR_14[cache_size=All,treshold=0.6] 41.8591 0.0015179 8.65122 0.28922
LR_14[cache_size=All,treshold=0.7] 1.01971 0 0.221567 3.15585e-05
LR_14[cache_size=All,treshold=0.8] 0.996072 0 0.21626 0
LR_14[cache_size=All,treshold=0.9] 0.98964 0 0.214784 0
LR_15[cache_size=0.001,treshold=0.3] 96.3873 96.2321 96.2876 96.2781
LR_15[cache_size=0.001,treshold=0.5] 85.2248 85.0531 85.1286 85.1284
LR_15[cache_size=0.001,treshold=0.6] 71.6985 71.619 71.6749 71.6917
LR_15[cache_size=0.001,treshold=0.7] 43.0687 42.8563 43.0001 43.0077
LR_15[cache_size=0.001,treshold=0.8] 0 0 0 0
LR_15[cache_size=0.001,treshold=0.9] 0 0 0 0
LR_15[cache_size=All,treshold=0.3] 98.6291 62.5759 86.6398 92.97
LR_15[cache_size=All,treshold=0.5] 76.5466 0.0168294 25.826 8.15949
LR_15[cache_size=All,treshold=0.6] 41.494 0.00192784 8.57445 0.267203
LR_15[cache_size=All,treshold=0.7] 1.02866 0 0.2232 5.25918e-05
LR_15[cache_size=All,treshold=0.8] 0.995167 0 0.215979 1.05184e-05
LR_15[cache_size=All,treshold=0.9] 0.984917 0 0.213844 0
LR_7[cache_size=0.001,treshold=0.3] 97.5571 97.4626 97.4992 97.4882
LR_7[cache_size=0.001,treshold=0.5] 93.7503 93.623 93.6585 93.6339
LR_7[cache_size=0.001,treshold=0.6] 87.1094 86.9658 87.0477 87.0595
LR_7[cache_size=0.001,treshold=0.7] 26.3669 25.9094 26.148 26.1589
LR_7[cache_size=0.001,treshold=0.8] 1.64238 1.59578 1.61903 1.6217
LR_7[cache_size=0.001,treshold=0.9] 0 0 0 0
LR_7[cache_size=All,treshold=0.3] 95.1715 72.7889 84.2368 85.8594
LR_7[cache_size=All,treshold=0.5] 73.1029 38.4053 56.871 61.8199
LR_7[cache_size=All,treshold=0.6] 58.3081 16.0942 36.825 31.9636
LR_7[cache_size=All,treshold=0.7] 53.2996 2.63038 24.5411 12.5872
LR_7[cache_size=All,treshold=0.8] 47.1457 0.168942 19.3419 6.2512
LR_7[cache_size=All,treshold=0.9] 37.938 0.00257741 14.5401 2.15885
LR_8[cache_size=0.001,treshold=0.3] 91.9068 91.6789 91.737 91.6959
LR_8[cache_size=0.001,treshold=0.5] 75.224 75.0761 75.1469 75.1551
LR_8[cache_size=0.001,treshold=0.6] 58.7067 58.5526 58.6331 58.6431
LR_8[cache_size=0.001,treshold=0.7] 33.7246 33.2856 33.5811 33.7083
LR_8[cache_size=0.001,treshold=0.8] 0.0280814 0.011942 0.0174121 0.0159978
LR_8[cache_size=0.001,treshold=0.9] 0 0 0 0
LR_8[cache_size=All,treshold=0.3] 95.1364 73.8602 84.4348 85.7619
LR_8[cache_size=All,treshold=0.5] 73.0882 38.2458 57.0313 61.8875
LR_8[cache_size=All,treshold=0.6] 59.4685 16.0466 37.0996 32.2961
LR_8[cache_size=All,treshold=0.7] 54.3847 2.6458 24.7665 12.5139
LR_8[cache_size=All,treshold=0.8] 48.4204 0.169078 19.594 6.2073
LR_8[cache_size=All,treshold=0.9] 38.7875 0.00256503 14.7166 2.13942
LR_9[cache_size=0.001,treshold=0.3] 96.3752 96.195 96.2502 96.2215
LR_9[cache_size=0.001,treshold=0.5] 85.1687 85.0145 85.0789 85.0477
LR_9[cache_size=0.001,treshold=0.6] 71.7115 71.6316 71.6629 71.6567
LR_9[cache_size=0.001,treshold=0.7] 43.1015 42.8623 43.0062 43.0327
LR_9[cache_size=0.001,treshold=0.8] 0 0 0 0
LR_9[cache_size=0.001,treshold=0.9] 0 0 0 0
LR_9[cache_size=All,treshold=0.3] 95.1994 71.6255 84.0063 85.9408
LR_9[cache_size=All,treshold=0.5] 73.0953 38.5439 56.6746 61.7484
LR_9[cache_size=All,treshold=0.6] 57.255 16.1337 36.5584 31.5905
LR_9[cache_size=All,treshold=0.7] 52.2616 2.61461 24.3469 12.6649
LR_9[cache_size=All,treshold=0.8] 46.1398 0.169103 19.1538 6.30023
LR_9[cache_size=All,treshold=0.9] 37.0043 0.00262691 14.3603 2.18227
LR_10[cache_size=0.01,treshold=0.3] 97.375 97.3163 97.3478 97.3536
LR_10[cache_size=0.01,treshold=0.5] 94.6888 94.6161 94.656 94.6633
LR_10[cache_size=0.01,treshold=0.6] 90.3682 90.2595 90.3135 90.3117
LR_10[cache_size=0.01,treshold=0.7] 6.03174 5.94003 6.00207 6.01526
LR_10[cache_size=0.01,treshold=0.8] 0.00050356 0 0.000241275 0.000200983
LR_10[cache_size=0.01,treshold=0.9] 0 0 0 0
LR_11[cache_size=0.01,treshold=0.3] 94.3315 94.2582 94.287 94.2818
LR_11[cache_size=0.01,treshold=0.5] 80.6643 80.5771 80.6194 80.6123
LR_11[cache_size=0.01,treshold=0.6] 66.8483 66.7207 66.7776 66.7719
LR_11[cache_size=0.01,treshold=0.7] 40.5801 40.509 40.5422 40.5384
LR_11[cache_size=0.01,treshold=0.8] 1.44608 1.41296 1.43248 1.43323
LR_11[cache_size=0.01,treshold=0.9] 0.00421799 0.0023063 0.00359838 0.00382705
LR_12[cache_size=0.01,treshold=0.3] 95.5653 95.4966 95.5278 95.521
LR_12[cache_size=0.01,treshold=0.5] 84.6144 84.5207 84.5513 84.5412
LR_12[cache_size=0.01,treshold=0.6] 71.4212 71.3477 71.3724 71.3584
LR_12[cache_size=0.01,treshold=0.7] 42.1164 42.0782 42.0978 42.1007
LR_12[cache_size=0.01,treshold=0.8] 1.42588 1.39571 1.41357 1.41188
LR_12[cache_size=0.01,treshold=0.9] 0.00713041 0.00401096 0.00576894 0.00613557
LR_13[cache_size=0.01,treshold=0.3] 97.3731 97.3151 97.3462 97.3519
LR_13[cache_size=0.01,treshold=0.5] 94.6805 94.6052 94.6481 94.657
LR_13[cache_size=0.01,treshold=0.6] 90.3742 90.2749 90.324 90.3247
LR_13[cache_size=0.01,treshold=0.7] 8.03698 8.00667 8.02649 8.03409
LR_13[cache_size=0.01,treshold=0.8] 0.000100712 0 2.01424e-05 0
LR_13[cache_size=0.01,treshold=0.9] 0 0 0 0
LR_14[cache_size=0.01,treshold=0.3] 93.9165 93.8404 93.8637 93.851
LR_14[cache_size=0.01,treshold=0.5] 81.5645 81.4569 81.4959 81.4904
LR_14[cache_size=0.01,treshold=0.6] 68.2926 68.2366 68.2604 68.249
LR_14[cache_size=0.01,treshold=0.7] 41.2829 41.1636 41.1976 41.1719
LR_14[cache_size=0.01,treshold=0.8] 2.83379 2.79279 2.80859 2.80884
LR_14[cache_size=0.01,treshold=0.9] 0.00210899 0.000802192 0.00156809 0.00161139
LR_15[cache_size=0.01,treshold=0.3] 95.6961 95.6312 95.6606 95.655
LR_15[cache_size=0.01,treshold=0.5] 85.2907 85.2006 85.2238 85.2046
LR_15[cache_size=0.01,treshold=0.6] 72.1813 72.103 72.1346 72.1318
LR_15[cache_size=0.01,treshold=0.7] 41.1227 41.0181 41.0454 41.0263
LR_15[cache_size=0.01,treshold=0.8] 2.16584 2.13363 2.14395 2.14157
LR_15[cache_size=0.01,treshold=0.9] 0.00200857 0.000701918 0.00146762 0.00160933
LR_7[cache_size=0.01,treshold=0.3] 97.3686 97.3096 97.3425 97.3482
LR_7[cache_size=0.01,treshold=0.5] 94.6936 94.6141 94.6562 94.6603
LR_7[cache_size=0.01,treshold=0.6] 90.3488 90.2492 90.2962 90.2923
LR_7[cache_size=0.01,treshold=0.7] 4.58652 4.53429 4.55233 4.54331
LR_7[cache_size=0.01,treshold=0.8] 0.000301475 0.000200548 0.000221094 0.000201166
LR_7[cache_size=0.01,treshold=0.9] 0 0 0 0
LR_8[cache_size=0.01,treshold=0.3] 94.2905 94.2105 94.2408 94.2346
LR_8[cache_size=0.01,treshold=0.5] 79.8408 79.7648 79.8063 79.7978
LR_8[cache_size=0.01,treshold=0.6] 66.1403 66.0341 66.092 66.086
LR_8[cache_size=0.01,treshold=0.7] 41.2065 41.1067 41.1406 41.1234
LR_8[cache_size=0.01,treshold=0.8] 0 0 0 0
LR_8[cache_size=0.01,treshold=0.9] 0 0 0 0
LR_9[cache_size=0.01,treshold=0.3] 95.4735 95.3989 95.4305 95.421
LR_9[cache_size=0.01,treshold=0.5] 83.9046 83.8062 83.8462 83.8416
LR_9[cache_size=0.01,treshold=0.6] 70.4536 70.3886 70.4178 70.413
LR_9[cache_size=0.01,treshold=0.7] 42.8521 42.7654 42.7949 42.774
LR_9[cache_size=0.01,treshold=0.8] 0 0 0 0
LR_9[cache_size=0.01,treshold=0.9] 0 0 0 0
LR_10[cache_size=0.1,treshold=0.3] 89.2643 89.2542 89.2601 89.263
LR_10[cache_size=0.1,treshold=0.5] 77.2598 77.2401 77.2519 77.2581
LR_10[cache_size=0.1,treshold=0.6] 62.1711 62.1222 62.1451 62.1468
LR_10[cache_size=0.1,treshold=0.7] 31.5959 31.5519 31.5796 31.5829
LR_10[cache_size=0.1,treshold=0.8] 2.13467 2.12937 2.13197 2.1317
LR_10[cache_size=0.1,treshold=0.9] 0.257826 0.253058 0.256527 0.257168
LR_11[cache_size=0.1,treshold=0.3] 89.1798 89.1671 89.1748 89.1782
LR_11[cache_size=0.1,treshold=0.5] 77.0769 77.0543 77.0672 77.0728
LR_11[cache_size=0.1,treshold=0.6] 62.1013 62.0506 62.0742 62.076
LR_11[cache_size=0.1,treshold=0.7] 31.6941 31.6538 31.6784 31.6804
LR_11[cache_size=0.1,treshold=0.8] 2.13293 2.12782 2.13011 2.12939
LR_11[cache_size=0.1,treshold=0.9] 0.262286 0.257266 0.260655 0.261218
LR_12[cache_size=0.1,treshold=0.3] 89.2823 89.2716 89.2776 89.2798
LR_12[cache_size=0.1,treshold=0.5] 77.3199 77.3019 77.3129 77.3191
LR_12[cache_size=0.1,treshold=0.6] 62.2521 62.2042 62.2253 62.2258
LR_12[cache_size=0.1,treshold=0.7] 31.5346 31.4921 31.519 31.5228
LR_12[cache_size=0.1,treshold=0.8] 2.09835 2.09459 2.09604 2.0948
LR_12[cache_size=0.1,treshold=0.9] 0.252683 0.24846 0.251711 0.252414
LR_13[cache_size=0.1,treshold=0.3] 85.7624 85.7447 85.7521 85.7507
LR_13[cache_size=0.1,treshold=0.5] 77.6022 77.5651 77.5868 77.5921
LR_13[cache_size=0.1,treshold=0.6] 68.6033 68.5457 68.5775 68.5855
LR_13[cache_size=0.1,treshold=0.7] 15.2344 15.1752 15.2046 15.2071
LR_13[cache_size=0.1,treshold=0.8] 0 0 0 0
LR_13[cache_size=0.1,treshold=0.9] 0 0 0 0
LR_14[cache_size=0.1,treshold=0.3] 85.7079 85.6903 85.698 85.6963
LR_14[cache_size=0.1,treshold=0.5] 76.0659 76.0278 76.0474 76.0461
LR_14[cache_size=0.1,treshold=0.6] 66.5266 66.4793 66.499 66.4994
LR_14[cache_size=0.1,treshold=0.7] 23.3943 23.3549 23.3742 23.371
LR_14[cache_size=0.1,treshold=0.8] 0 0 0 0
LR_14[cache_size=0.1,treshold=0.9] 0 0 0 0
LR_15[cache_size=0.1,treshold=0.3] 85.7083 85.6905 85.6983 85.6966
LR_15[cache_size=0.1,treshold=0.5] 76.0658 76.0278 76.0474 76.0461
LR_15[cache_size=0.1,treshold=0.6] 66.5255 66.4775 66.4974 66.4975
LR_15[cache_size=0.1,treshold=0.7] 23.5234 23.4831 23.5022 23.4977
LR_15[cache_size=0.1,treshold=0.8] 0 0 0 0
LR_15[cache_size=0.1,treshold=0.9] 0 0 0 0
LR_7[cache_size=0.1,treshold=0.3] 89.4207 89.4013 89.4085 89.404
LR_7[cache_size=0.1,treshold=0.5] 74.6101 74.5765 74.5935 74.5995
LR_7[cache_size=0.1,treshold=0.6] 59.0326 58.9805 59.0047 59.0117
LR_7[cache_size=0.1,treshold=0.7] 28.4263 28.3778 28.4064 28.4082
LR_7[cache_size=0.1,treshold=0.8] 0 0 0 0
LR_7[cache_size=0.1,treshold=0.9] 0 0 0 0
LR_8[cache_size=0.1,treshold=0.3] 87.8624 87.8457 87.8534 87.8523
LR_8[cache_size=0.1,treshold=0.5] 71.306 71.2659 71.2896 71.2975
LR_8[cache_size=0.1,treshold=0.6] 56.6264 56.5704 56.5977 56.6045
LR_8[cache_size=0.1,treshold=0.7] 31.677 31.6262 31.6543 31.6554
LR_8[cache_size=0.1,treshold=0.8] 0 0 0 0
LR_8[cache_size=0.1,treshold=0.9] 0 0 0 0
LR_9[cache_size=0.1,treshold=0.3] 87.9638 87.9473 87.9551 87.9535
LR_9[cache_size=0.1,treshold=0.5] 71.4639 71.4227 71.4479 71.4568
LR_9[cache_size=0.1,treshold=0.6] 56.7316 56.6757 56.7036 56.7094
LR_9[cache_size=0.1,treshold=0.7] 31.5653 31.513 31.5425 31.5428
LR_9[cache_size=0.1,treshold=0.8] 0 0 0 0
LR_9[cache_size=0.1,treshold=0.9] 0 0 0 0
LR_10[cache_size=0.2,treshold=0.3] 83.5961 83.5694 83.5792 83.5753
LR_10[cache_size=0.2,treshold=0.5] 68.5525 68.5371 68.545 68.5465
LR_10[cache_size=0.2,treshold=0.6] 55.0807 55.0695 55.073 55.0709
LR_10[cache_size=0.2,treshold=0.7] 20.0306 20.0094 20.0186 20.0145
LR_10[cache_size=0.2,treshold=0.8] 0 0 0 0
LR_10[cache_size=0.2,treshold=0.9] 0 0 0 0
LR_11[cache_size=0.2,treshold=0.3] 83.6025 83.5758 83.5855 83.5816
LR_11[cache_size=0.2,treshold=0.5] 68.9088 68.8911 68.8993 68.901
LR_11[cache_size=0.2,treshold=0.6] 55.2445 55.2327 55.2358 55.2336
LR_11[cache_size=0.2,treshold=0.7] 19.5682 19.5445 19.5556 19.5541
LR_11[cache_size=0.2,treshold=0.8] 0 0 0 0
LR_11[cache_size=0.2,treshold=0.9] 0 0 0 0
LR_12[cache_size=0.2,treshold=0.3] 83.5937 83.5671 83.5768 83.5727
LR_12[cache_size=0.2,treshold=0.5] 69.2713 69.2555 69.2636 69.2649
LR_12[cache_size=0.2,treshold=0.6] 55.3333 55.3201 55.3243 55.3227
LR_12[cache_size=0.2,treshold=0.7] 19.1504 19.1237 19.1382 19.1369
LR_12[cache_size=0.2,treshold=0.8] 0 0 0 0
LR_12[cache_size=0.2,treshold=0.9] 0 0 0 0
LR_13[cache_size=0.2,treshold=0.3] 85.1814 85.1577 85.167 85.1645
LR_13[cache_size=0.2,treshold=0.5] 67.1231 67.1173 67.1204 67.1213
LR_13[cache_size=0.2,treshold=0.6] 49.1877 49.1653 49.1735 49.1699
LR_13[cache_size=0.2,treshold=0.7] 17.1856 17.1694 17.1774 17.1748
LR_13[cache_size=0.2,treshold=0.8] 0.00191122 0.00171103 0.00182223 0.00184962
LR_13[cache_size=0.2,treshold=0.9] 0.000725711 0.000609103 0.000666862 0.000670311
LR_14[cache_size=0.2,treshold=0.3] 85.1966 85.174 85.1825 85.1797
LR_14[cache_size=0.2,treshold=0.5] 67.0779 67.0718 67.0754 67.0765
LR_14[cache_size=0.2,treshold=0.6] 49.0908 49.0709 49.0774 49.073
LR_14[cache_size=0.2,treshold=0.7] 17.0192 17.0031 17.0112 17.0085
LR_14[cache_size=0.2,treshold=0.8] 0 0 0 0
LR_14[cache_size=0.2,treshold=0.9] 0 0 0 0
LR_15[cache_size=0.2,treshold=0.3] 85.2582 85.2335 85.2436 85.2404
LR_15[cache_size=0.2,treshold=0.5] 67.1184 67.1115 67.1154 67.1163
LR_15[cache_size=0.2,treshold=0.6] 49.114 49.0932 49.1003 49.0966
LR_15[cache_size=0.2,treshold=0.7] 16.8604 16.847 16.8534 16.8522
LR_15[cache_size=0.2,treshold=0.8] 0 0 0 0
LR_15[cache_size=0.2,treshold=0.9] 0 0 0 0
LR_7[cache_size=0.2,treshold=0.3] 83.7699 83.747 83.755 83.7504
LR_7[cache_size=0.2,treshold=0.5] 64.4387 64.4283 64.4317 64.43
LR_7[cache_size=0.2,treshold=0.6] 47.9629 47.9344 47.9486 47.9476
LR_7[cache_size=0.2,treshold=0.7] 20.5382 20.516 20.5278 20.525
LR_7[cache_size=0.2,treshold=0.8] 0.000714631 0.000564855 0.000634739 0.000631533
LR_7[cache_size=0.2,treshold=0.9] 4.9858e-05 2.21512e-05 3.54487e-05 3.3232e-05
LR_8[cache_size=0.2,treshold=0.3] 83.9088 83.8831 83.8913 83.8872
LR_8[cache_size=0.2,treshold=0.5] 64.5758 64.5667 64.5704 64.5701
LR_8[cache_size=0.2,treshold=0.6] 47.9949 47.9657 47.9799 47.9789
LR_8[cache_size=0.2,treshold=0.7] 20.2506 20.2309 20.2397 20.2356
LR_8[cache_size=0.2,treshold=0.8] 0 0 0 0
LR_8[cache_size=0.2,treshold=0.9] 0 0 0 0
LR_9[cache_size=0.2,treshold=0.3] 83.9717 83.9454 83.9533 83.9483
LR_9[cache_size=0.2,treshold=0.5] 64.6332 64.6245 64.6284 64.629
LR_9[cache_size=0.2,treshold=0.6] 47.9965 47.9664 47.9809 47.9793
LR_9[cache_size=0.2,treshold=0.7] 20.0841 20.066 20.0744 20.0708
LR_9[cache_size=0.2,treshold=0.8] 0 0 0 0
LR_9[cache_size=0.2,treshold=0.9] 0 0 0 0
LR_10[cache_size=0.4,treshold=0.3] 76.9303 76.908 76.9145 76.9106
LR_10[cache_size=0.4,treshold=0.5] 50.9489 50.9349 50.9438 50.9464
LR_10[cache_size=0.4,treshold=0.6] 34.15 34.1391 34.1443 34.1449
LR_10[cache_size=0.4,treshold=0.7] 9.13262 9.11202 9.12143 9.11759
LR_10[cache_size=0.4,treshold=0.8] 0.0186612 0.017784 0.0181582 0.0181346
LR_10[cache_size=0.4,treshold=0.9] 0.0109344 0.0102446 0.0105435 0.0104426
LR_11[cache_size=0.4,treshold=0.3] 77.1578 77.0879 77.1189 77.1225
LR_11[cache_size=0.4,treshold=0.5] 50.9136 50.8969 50.9072 50.9101
LR_11[cache_size=0.4,treshold=0.6] 33.9787 33.9651 33.9714 33.9717
LR_11[cache_size=0.4,treshold=0.7] 8.73736 8.64091 8.68815 8.69015
LR_11[cache_size=0.4,treshold=0.8] 0.00832935 0.00766682 0.00807639 0.00805432
LR_11[cache_size=0.4,treshold=0.9] 0.00205078 0.00181006 0.00189812 0.00188746
LR_12[cache_size=0.4,treshold=0.3] 77.2316 77.2054 77.2139 77.2129
LR_12[cache_size=0.4,treshold=0.5] 50.9266 50.9126 50.9215 50.9242
LR_12[cache_size=0.4,treshold=0.6] 33.9334 33.9216 33.9271 33.9277
LR_12[cache_size=0.4,treshold=0.7] 8.54139 8.51295 8.52589 8.52181
LR_12[cache_size=0.4,treshold=0.8] 0.00810039 0.00762969 0.00791551 0.00798041
LR_12[cache_size=0.4,treshold=0.9] 0.00197345 0.00178531 0.00186192 0.00184709
LR_13[cache_size=0.4,treshold=0.3] 79.7959 79.7707 79.7821 79.7794
LR_13[cache_size=0.4,treshold=0.5] 56.8821 56.8772 56.8796 56.8796
LR_13[cache_size=0.4,treshold=0.6] 37.4317 37.4198 37.4265 37.4261
LR_13[cache_size=0.4,treshold=0.7] 4.59219 4.56944 4.58143 4.58078
LR_13[cache_size=0.4,treshold=0.8] 0.00822766 0.00764558 0.00791799 0.00784122
LR_13[cache_size=0.4,treshold=0.9] 0.00372859 0.00342191 0.00353946 0.00352004
LR_14[cache_size=0.4,treshold=0.3] 79.7923 79.7675 79.7787 79.7763
LR_14[cache_size=0.4,treshold=0.5] 56.8712 56.8663 56.8686 56.8685
LR_14[cache_size=0.4,treshold=0.6] 37.4622 37.4499 37.4573 37.4572
LR_14[cache_size=0.4,treshold=0.7] 4.6881 4.66267 4.67491 4.67321
LR_14[cache_size=0.4,treshold=0.8] 0.00791513 0.00743518 0.00766738 0.00765872
LR_14[cache_size=0.4,treshold=0.9] 0.00371931 0.00340026 0.00353265 0.00352004
LR_15[cache_size=0.4,treshold=0.3] 79.8184 79.7927 79.8045 79.8023
LR_15[cache_size=0.4,treshold=0.5] 56.8987 56.8941 56.8963 56.8963
LR_15[cache_size=0.4,treshold=0.6] 37.4239 37.4122 37.4186 37.4181
LR_15[cache_size=0.4,treshold=0.7] 4.51422 4.49214 4.50309 4.50226
LR_15[cache_size=0.4,treshold=0.8] 0.00824003 0.00772293 0.00794398 0.00786287
LR_15[cache_size=0.4,treshold=0.9] 0.00371621 0.00339407 0.00352523 0.00350458
LR_7[cache_size=0.4,treshold=0.3] 82.6636 82.6517 82.6574 82.6576
LR_7[cache_size=0.4,treshold=0.5] 58.8613 58.8492 58.856 58.8576
LR_7[cache_size=0.4,treshold=0.6] 36.525 36.509 36.5186 36.5205
LR_7[cache_size=0.4,treshold=0.7] 0.0598249 0.0588934 0.0593094 0.0591997
LR_7[cache_size=0.4,treshold=0.8] 0.016233 0.0157954 0.0159684 0.015879
LR_7[cache_size=0.4,treshold=0.9] 0.0138327 0.0131252 0.0134153 0.0133349
LR_8[cache_size=0.4,treshold=0.3] 82.9483 82.9326 82.9406 82.9413
LR_8[cache_size=0.4,treshold=0.5] 59.0477 59.034 59.0413 59.0426
LR_8[cache_size=0.4,treshold=0.6] 36.3088 36.2915 36.3009 36.3037
LR_8[cache_size=0.4,treshold=0.7] 0.0377267 0.0364858 0.0368858 0.0365835
LR_8[cache_size=0.4,treshold=0.8] 0 0 0 0
LR_8[cache_size=0.4,treshold=0.9] 0 0 0 0
LR_9[cache_size=0.4,treshold=0.3] 83.0086 82.9942 83.0019 83.003
LR_9[cache_size=0.4,treshold=0.5] 59.0808 59.0669 59.0739 59.0748
LR_9[cache_size=0.4,treshold=0.6] 36.2503 36.2326 36.2417 36.243
LR_9[cache_size=0.4,treshold=0.7] 0.0369191 0.0353162 0.0359428 0.0356269
LR_9[cache_size=0.4,treshold=0.8] 0 0 0 0
LR_9[cache_size=0.4,treshold=0.9] 0 0 0 0
Offline Clock 1st iteration 0 0 0 0
Offline Clock 2nd iteration 99.8119 59.132 82.3408 83.126
Zipf Optimal Distribution 99.9168 54.4937 83.9515 89.1265

Miss Ratio Reduced (%)

Model Max Min Avg Mdn
LR_10[cache_size=0.001,treshold=0.3] 0 0 0 0
LR_10[cache_size=0.001,treshold=0.5] 0 0 0 0
LR_10[cache_size=0.001,treshold=0.6] 0 0 0 0
LR_10[cache_size=0.001,treshold=0.7] 0 0 0 0
LR_10[cache_size=0.001,treshold=0.8] 0 0 0 0
LR_10[cache_size=0.001,treshold=0.9] 0 0 0 0
LR_10[cache_size=All,treshold=0.3] 0.00798719 -0.00362421 0.00086107 0.000202019
LR_10[cache_size=All,treshold=0.5] 0.00565776 -0.0019968 0.000724704 0.000101011
LR_10[cache_size=All,treshold=0.6] 0.00815363 -0.00183045 0.000486782 0
LR_10[cache_size=All,treshold=0.7] 0.00249601 -0.00282888 -1.46201e-05 0
LR_10[cache_size=All,treshold=0.8] 0.000333323 -0.000332784 1.1821e-05 0
LR_10[cache_size=All,treshold=0.9] 0.000444431 -0.000222218 -1.34833e-05 0
LR_11[cache_size=0.001,treshold=0.3] 0 0 0 0
LR_11[cache_size=0.001,treshold=0.5] 0 0 0 0
LR_11[cache_size=0.001,treshold=0.6] 0 0 0 0
LR_11[cache_size=0.001,treshold=0.7] 0 0 0 0
LR_11[cache_size=0.001,treshold=0.8] 0 0 0 0
LR_11[cache_size=0.001,treshold=0.9] 0 0 0 0
LR_11[cache_size=All,treshold=0.3] 0.00798719 -0.00374918 0.000828169 0.000202019
LR_11[cache_size=All,treshold=0.5] 0.00582416 -0.001664 0.000733458 0
LR_11[cache_size=All,treshold=0.6] 0.00881924 -0.00249607 0.000439082 0
LR_11[cache_size=All,treshold=0.7] 0.00299521 -0.00183045 0.000116297 0
LR_11[cache_size=All,treshold=0.8] 0.000499202 -0.0003328 6.41822e-06 0
LR_11[cache_size=All,treshold=0.9] 0.000444431 -0.000333327 -1.34835e-05 0
LR_12[cache_size=0.001,treshold=0.3] 0 0 0 0
LR_12[cache_size=0.001,treshold=0.5] 0 0 0 0
LR_12[cache_size=0.001,treshold=0.6] 0 0 0 0
LR_12[cache_size=0.001,treshold=0.7] 0 0 0 0
LR_12[cache_size=0.001,treshold=0.8] 0 0 0 0
LR_12[cache_size=0.001,treshold=0.9] 0 0 0 0
LR_12[cache_size=All,treshold=0.3] 0.00798719 -0.00362421 0.000874789 0.000202019
LR_12[cache_size=All,treshold=0.5] 0.00582416 -0.0014976 0.00073348 0
LR_12[cache_size=All,treshold=0.6] 0.00881924 -0.00332809 0.000474746 0
LR_12[cache_size=All,treshold=0.7] 0.0014976 -0.00133124 3.36536e-05 0
LR_12[cache_size=All,treshold=0.8] 0.000499202 -0.0003328 1.50536e-05 0
LR_12[cache_size=All,treshold=0.9] 0.000333323 -0.000222218 -9.03926e-06 0
LR_13[cache_size=0.001,treshold=0.3] 0 0 0 0
LR_13[cache_size=0.001,treshold=0.5] 0 0 0 0
LR_13[cache_size=0.001,treshold=0.6] 0 0 0 0
LR_13[cache_size=0.001,treshold=0.7] 0 0 0 0
LR_13[cache_size=0.001,treshold=0.8] 0 0 0 0
LR_13[cache_size=0.001,treshold=0.9] 0 0 0 0
LR_13[cache_size=All,treshold=0.3] 0.00815359 -0.00349923 0.000893184 0.000202019
LR_13[cache_size=All,treshold=0.5] 0.00798742 -0.0027494 0.000570512 0
LR_13[cache_size=All,treshold=0.6] 0.00698883 -0.00232966 0.000463697 0
LR_13[cache_size=All,treshold=0.7] 0 -0.000101011 -4.04044e-06 0
LR_13[cache_size=All,treshold=0.8] 0 0 0 0
LR_13[cache_size=All,treshold=0.9] 0 0 0 0
LR_14[cache_size=0.001,treshold=0.3] 0 0 0 0
LR_14[cache_size=0.001,treshold=0.5] 0 0 0 0
LR_14[cache_size=0.001,treshold=0.6] 0 0 0 0
LR_14[cache_size=0.001,treshold=0.7] 0 0 0 0
LR_14[cache_size=0.001,treshold=0.8] 0 0 0 0
LR_14[cache_size=0.001,treshold=0.9] 0 0 0 0
LR_14[cache_size=All,treshold=0.3] 0.00765439 -0.00362421 0.000956058 0.000303024
LR_14[cache_size=All,treshold=0.5] 0.00798742 -0.0027494 0.000578826 0
LR_14[cache_size=All,treshold=0.6] 0.00815363 -0.00216326 0.000490321 0
LR_14[cache_size=All,treshold=0.7] 0 0 0 0
LR_14[cache_size=All,treshold=0.8] 0 0 0 0
LR_14[cache_size=All,treshold=0.9] 0 0 0 0
LR_15[cache_size=0.001,treshold=0.3] 0 0 0 0
LR_15[cache_size=0.001,treshold=0.5] 0 0 0 0
LR_15[cache_size=0.001,treshold=0.6] 0 0 0 0
LR_15[cache_size=0.001,treshold=0.7] 0 0 0 0
LR_15[cache_size=0.001,treshold=0.8] 0 0 0 0
LR_15[cache_size=0.001,treshold=0.9] 0 0 0 0
LR_15[cache_size=All,treshold=0.3] 0.00732159 -0.00362421 0.000975453 0.000303024
LR_15[cache_size=All,treshold=0.5] 0.00798742 -0.0027494 0.000577169 0
LR_15[cache_size=All,treshold=0.6] 0.00798723 -0.00266247 0.00045704 0
LR_15[cache_size=All,treshold=0.7] 0 0 0 0
LR_15[cache_size=All,treshold=0.8] 0 -0.000101011 -4.04044e-06 0
LR_15[cache_size=All,treshold=0.9] 0 0 0 0
LR_7[cache_size=0.001,treshold=0.3] 0 0 0 0
LR_7[cache_size=0.001,treshold=0.5] 0 0 0 0
LR_7[cache_size=0.001,treshold=0.6] 0 0 0 0
LR_7[cache_size=0.001,treshold=0.7] 0 -0.0001001 -2.002e-05 0
LR_7[cache_size=0.001,treshold=0.8] 0 0 0 0
LR_7[cache_size=0.001,treshold=0.9] 0 0 0 0
LR_7[cache_size=All,treshold=0.3] 0.00499176 -0.0038742 0.000645072 0.000303024
LR_7[cache_size=All,treshold=0.5] 0.00981787 -0.00399918 0.000555027 0.000101009
LR_7[cache_size=All,treshold=0.6] 0.00532482 -0.00188883 0.000320982 0
LR_7[cache_size=All,treshold=0.7] 0.00149761 -0.00155551 -9.70986e-05 0
LR_7[cache_size=All,treshold=0.8] 0.000555525 -0.000888862 -1.58246e-05 0
LR_7[cache_size=All,treshold=0.9] 0.000124961 -0.000249935 -3.27375e-05 0
LR_8[cache_size=0.001,treshold=0.3] 0 0 0 0
LR_8[cache_size=0.001,treshold=0.5] 0 0 0 0
LR_8[cache_size=0.001,treshold=0.6] 0 0 0 0
LR_8[cache_size=0.001,treshold=0.7] 0 0 0 0
LR_8[cache_size=0.001,treshold=0.8] 0 0 0 0
LR_8[cache_size=0.001,treshold=0.9] 0 0 0 0
LR_8[cache_size=All,treshold=0.3] 0.00549094 -0.0038742 0.000693896 0.000303024
LR_8[cache_size=All,treshold=0.5] 0.00998427 -0.00399918 0.000548179 0.000101009
LR_8[cache_size=All,treshold=0.6] 0.00582402 -0.00188883 0.000281043 0
LR_8[cache_size=All,treshold=0.7] 0.00149761 -0.00166662 -8.65525e-05 0
LR_8[cache_size=All,treshold=0.8] 0.00066663 -0.000888862 -1.6379e-05 0
LR_8[cache_size=All,treshold=0.9] 0.000124961 -0.000249935 -3.27373e-05 0
LR_9[cache_size=0.001,treshold=0.3] 0 0 0 0
LR_9[cache_size=0.001,treshold=0.5] 0 0 0 0
LR_9[cache_size=0.001,treshold=0.6] 0 0 0 0
LR_9[cache_size=0.001,treshold=0.7] 0 0 0 0
LR_9[cache_size=0.001,treshold=0.8] 0 0 0 0
LR_9[cache_size=0.001,treshold=0.9] 0 0 0 0
LR_9[cache_size=All,treshold=0.3] 0.00499176 -0.00362425 0.000674895 0.000303024
LR_9[cache_size=All,treshold=0.5] 0.00965147 -0.00399918 0.0005532 0.000101009
LR_9[cache_size=All,treshold=0.6] 0.00482562 -0.00188883 0.000285484 0
LR_9[cache_size=All,treshold=0.7] 0.00133121 -0.00166662 -9.98647e-05 0
LR_9[cache_size=All,treshold=0.8] 0.00066663 -0.000888862 -9.16771e-06 0
LR_9[cache_size=All,treshold=0.9] 0.000124961 -0.000249935 -3.27375e-05 0
LR_10[cache_size=0.01,treshold=0.3] 0.000303024 -0.000202021 0.000101009 0.000101012
LR_10[cache_size=0.01,treshold=0.5] 0.000303024 -0.000202021 0.000101009 0.000101012
LR_10[cache_size=0.01,treshold=0.6] 0.000303024 -0.000202021 0.000101009 0.000101012
LR_10[cache_size=0.01,treshold=0.7] 0 -0.000101011 -4.04041e-05 0
LR_10[cache_size=0.01,treshold=0.8] 0 0 0 0
LR_10[cache_size=0.01,treshold=0.9] 0 0 0 0
LR_11[cache_size=0.01,treshold=0.3] 0.000404032 -0.000202021 0.000121211 0.000101012
LR_11[cache_size=0.01,treshold=0.5] 0.000303024 -0.000202021 8.08066e-05 0.000101011
LR_11[cache_size=0.01,treshold=0.6] 0.000202016 -0.000202021 4.04031e-05 0.000101009
LR_11[cache_size=0.01,treshold=0.7] 0.000202019 0 6.06053e-05 0
LR_11[cache_size=0.01,treshold=0.8] 0 0 0 0
LR_11[cache_size=0.01,treshold=0.9] 0 0 0 0
LR_12[cache_size=0.01,treshold=0.3] 0.000303024 -0.000202021 0.000101009 0.000101012
LR_12[cache_size=0.01,treshold=0.5] 0.000303024 -0.000202021 8.08066e-05 0.000101011
LR_12[cache_size=0.01,treshold=0.6] 0.000202016 -0.000202021 4.04031e-05 0.000101009
LR_12[cache_size=0.01,treshold=0.7] 0.000202019 0 6.06053e-05 0
LR_12[cache_size=0.01,treshold=0.8] 0 0 0 0
LR_12[cache_size=0.01,treshold=0.9] 0 0 0 0
LR_13[cache_size=0.01,treshold=0.3] 0.000303024 -0.000202021 0.000101009 0.000101012
LR_13[cache_size=0.01,treshold=0.5] 0.000303024 -0.000202021 0.000101009 0.000101012
LR_13[cache_size=0.01,treshold=0.6] 0.000303024 -0.000202021 0.000101009 0.000101012
LR_13[cache_size=0.01,treshold=0.7] 0 -0.000101011 -4.04041e-05 0
LR_13[cache_size=0.01,treshold=0.8] 0 0 0 0
LR_13[cache_size=0.01,treshold=0.9] 0 0 0 0
LR_14[cache_size=0.01,treshold=0.3] 0.000404032 -0.000202021 0.000121211 0.000101012
LR_14[cache_size=0.01,treshold=0.5] 0.000303024 -0.000202021 8.08066e-05 0.000101011
LR_14[cache_size=0.01,treshold=0.6] 0.000202016 -0.000202021 4.04031e-05 0.000101009
LR_14[cache_size=0.01,treshold=0.7] 0.000202019 0 0.00010101 0.000101011
LR_14[cache_size=0.01,treshold=0.8] 0 -0.000101012 -2.02025e-05 0
LR_14[cache_size=0.01,treshold=0.9] 0 0 0 0
LR_15[cache_size=0.01,treshold=0.3] 0.000303024 -0.000202021 0.000101009 0.000101012
LR_15[cache_size=0.01,treshold=0.5] 0.000303024 -0.000202021 8.08066e-05 0.000101011
LR_15[cache_size=0.01,treshold=0.6] 0.000202016 -0.000202021 4.04031e-05 0.000101009
LR_15[cache_size=0.01,treshold=0.7] 0.000202019 0 0.00010101 0.000101011
LR_15[cache_size=0.01,treshold=0.8] 0 -0.000101011 -4.04041e-05 0
LR_15[cache_size=0.01,treshold=0.9] 0 0 0 0
LR_7[cache_size=0.01,treshold=0.3] 0.000303024 -0.000202021 0.000101009 0.000101012
LR_7[cache_size=0.01,treshold=0.5] 0.000303024 -0.000202021 0.000101009 0.000101012
LR_7[cache_size=0.01,treshold=0.6] 0.000303024 -0.000202021 0.000101009 0.000101012
LR_7[cache_size=0.01,treshold=0.7] 0 0 0 0
LR_7[cache_size=0.01,treshold=0.8] 0 0 0 0
LR_7[cache_size=0.01,treshold=0.9] 0 0 0 0
LR_8[cache_size=0.01,treshold=0.3] 0.000404032 -0.000202021 0.000121211 0.000101012
LR_8[cache_size=0.01,treshold=0.5] 0.000303024 -0.000202021 0.000101009 0.000101012
LR_8[cache_size=0.01,treshold=0.6] 0.000202016 -0.000202021 4.04031e-05 0.000101009
LR_8[cache_size=0.01,treshold=0.7] 0.000202019 0 0.000101009 0.000101011
LR_8[cache_size=0.01,treshold=0.8] 0 0 0 0
LR_8[cache_size=0.01,treshold=0.9] 0 0 0 0
LR_9[cache_size=0.01,treshold=0.3] 0.000303024 -0.000202021 0.000101009 0.000101012
LR_9[cache_size=0.01,treshold=0.5] 0.000303024 -0.000202021 0.000101009 0.000101012
LR_9[cache_size=0.01,treshold=0.6] 0.000202016 -0.00010101 8.08077e-05 0.000101011
LR_9[cache_size=0.01,treshold=0.7] 0.000202019 0 0.000101009 0.000101011
LR_9[cache_size=0.01,treshold=0.8] 0 0 0 0
LR_9[cache_size=0.01,treshold=0.9] 0 0 0 0
LR_10[cache_size=0.1,treshold=0.3] 0.000777762 -0.00211105 0.000133324 0.000666628
LR_10[cache_size=0.1,treshold=0.5] 0.000999978 -0.000888862 0.000288878 0.000555544
LR_10[cache_size=0.1,treshold=0.6] 0.000555523 -0.000888862 -2.22221e-05 0.000111109
LR_10[cache_size=0.1,treshold=0.7] 0.000777735 -0.00099997 -2.22259e-05 0.000111105
LR_10[cache_size=0.1,treshold=0.8] 0.000111109 -0.000111105 2.22218e-05 0
LR_10[cache_size=0.1,treshold=0.9] 0.000111109 -0.000111109 -2.22209e-05 0
LR_11[cache_size=0.1,treshold=0.3] 0.000777733 -0.00211105 0.000111102 0.00066663
LR_11[cache_size=0.1,treshold=0.5] 0.000999978 -0.00099997 0.000266657 0.000555544
LR_11[cache_size=0.1,treshold=0.6] 0.000444435 -0.000888862 -4.4443e-05 0.000111109
LR_11[cache_size=0.1,treshold=0.7] 0.000777735 -0.00099997 -2.22259e-05 0.000111105
LR_11[cache_size=0.1,treshold=0.8] 0.000111109 -0.000111105 2.22218e-05 0
LR_11[cache_size=0.1,treshold=0.9] 0.000111109 -0.000111109 -2.22209e-05 0
LR_12[cache_size=0.1,treshold=0.3] 0.000777762 -0.00211105 0.000133324 0.000666628
LR_12[cache_size=0.1,treshold=0.5] 0.000999978 -0.00099997 0.000266657 0.000555544
LR_12[cache_size=0.1,treshold=0.6] 0.000555523 -0.000888862 -6.66656e-05 0
LR_12[cache_size=0.1,treshold=0.7] 0.000777735 -0.00111108 -3.13551e-09 0
LR_12[cache_size=0.1,treshold=0.8] 0.000111105 -0.000111109 -2.22217e-05 0
LR_12[cache_size=0.1,treshold=0.9] 0.000111109 -0.000111109 -2.22209e-05 0
LR_13[cache_size=0.1,treshold=0.3] 0.00122215 -0.00222216 6.66594e-05 0.000333327
LR_13[cache_size=0.1,treshold=0.5] 0.00133326 -0.000777754 0.000399985 0.000777762
LR_13[cache_size=0.1,treshold=0.6] 0.00111109 -0.00099997 0.000355539 0.00044442
LR_13[cache_size=0.1,treshold=0.7] 0.000555525 -0.00233326 -0.000511093 0
LR_13[cache_size=0.1,treshold=0.8] 0 0 0 0
LR_13[cache_size=0.1,treshold=0.9] 0 0 0 0
LR_14[cache_size=0.1,treshold=0.3] 0.00122215 -0.00222216 8.88804e-05 0.000333327
LR_14[cache_size=0.1,treshold=0.5] 0.00111105 -0.000777754 0.000355543 0.000666653
LR_14[cache_size=0.1,treshold=0.6] 0.0012222 -0.000666647 0.000399981 0.000555525
LR_14[cache_size=0.1,treshold=0.7] 0.000777735 -0.00233326 -0.000333324 0.000111109
LR_14[cache_size=0.1,treshold=0.8] 0 0 0 0
LR_14[cache_size=0.1,treshold=0.9] 0 0 0 0
LR_15[cache_size=0.1,treshold=0.3] 0.00122215 -0.00222216 8.88804e-05 0.000333327
LR_15[cache_size=0.1,treshold=0.5] 0.00111105 -0.000777754 0.000355543 0.000666653
LR_15[cache_size=0.1,treshold=0.6] 0.0012222 -0.000777754 0.00037776 0.000555525
LR_15[cache_size=0.1,treshold=0.7] 0.00066663 -0.00222216 -0.000333324 0.000111109
LR_15[cache_size=0.1,treshold=0.8] 0 0 0 0
LR_15[cache_size=0.1,treshold=0.9] 0 0 0 0
LR_7[cache_size=0.1,treshold=0.3] 0.000777733 -0.00211105 8.88807e-05 0.00066663
LR_7[cache_size=0.1,treshold=0.5] 0.0013333 -0.000888862 0.000399983 0.000222218
LR_7[cache_size=0.1,treshold=0.6] 0.000666652 -0.00099997 -1.65414e-09 0
LR_7[cache_size=0.1,treshold=0.7] 0.00066663 -0.00155551 -0.000155551 0.000111109
LR_7[cache_size=0.1,treshold=0.8] 0 0 0 0
LR_7[cache_size=0.1,treshold=0.9] 0 0 0 0
LR_8[cache_size=0.1,treshold=0.3] 0.00111105 -0.00211105 0.000133322 0.000555543
LR_8[cache_size=0.1,treshold=0.5] 0.0013333 -0.000888862 0.000511088 0.000555525
LR_8[cache_size=0.1,treshold=0.6] 0.00077776 -0.00099997 0.000111107 0.000333314
LR_8[cache_size=0.1,treshold=0.7] 0.000999946 -0.000666647 0.000111102 0.000111105
LR_8[cache_size=0.1,treshold=0.8] 0 0 0 0
LR_8[cache_size=0.1,treshold=0.9] 0 0 0 0
LR_9[cache_size=0.1,treshold=0.3] 0.00111105 -0.00211105 0.000155543 0.00066663
LR_9[cache_size=0.1,treshold=0.5] 0.0012222 -0.000666647 0.00053331 0.000555525
LR_9[cache_size=0.1,treshold=0.6] 0.000888869 -0.00111108 0.000133328 0.000333314
LR_9[cache_size=0.1,treshold=0.7] 0.000999946 -0.000777754 8.88818e-05 0
LR_9[cache_size=0.1,treshold=0.8] 0 0 0 0
LR_9[cache_size=0.1,treshold=0.9] 0 0 0 0
LR_10[cache_size=0.2,treshold=0.3] 0.00349909 -0.00424912 -0.000724897 -0.000124961
LR_10[cache_size=0.2,treshold=0.5] 0.00149954 -0.00312436 -0.000449951 0.000249922
LR_10[cache_size=0.2,treshold=0.6] 0.00299907 -0.00299938 -8.26455e-08 0.000249922
LR_10[cache_size=0.2,treshold=0.7] 0.00149954 -0.00112477 0.000349862 0.000374903
LR_10[cache_size=0.2,treshold=0.8] 0 0 0 0
LR_10[cache_size=0.2,treshold=0.9] 0 0 0 0
LR_11[cache_size=0.2,treshold=0.3] 0.00349909 -0.00424912 -0.00074989 -0.000124961
LR_11[cache_size=0.2,treshold=0.5] 0.0016245 -0.00274943 -0.000324982 0.000374883
LR_11[cache_size=0.2,treshold=0.6] 0.00274915 -0.00312436 -7.50634e-05 0.000374883
LR_11[cache_size=0.2,treshold=0.7] 0.00149954 -0.00124974 0.000324872 0.000749805
LR_11[cache_size=0.2,treshold=0.8] 0 0 0 0
LR_11[cache_size=0.2,treshold=0.9] 0 0 0 0
LR_12[cache_size=0.2,treshold=0.3] 0.00349909 -0.00412415 -0.000749887 -0.000249923
LR_12[cache_size=0.2,treshold=0.5] 0.00137464 -0.00262446 -0.000324979 0.000499844
LR_12[cache_size=0.2,treshold=0.6] 0.00274915 -0.00312436 -2.50753e-05 0.000374883
LR_12[cache_size=0.2,treshold=0.7] 0.00137458 -0.000999794 0.000374866 0.000749805
LR_12[cache_size=0.2,treshold=0.8] 0 0 0 0
LR_12[cache_size=0.2,treshold=0.9] 0 0 0 0
LR_13[cache_size=0.2,treshold=0.3] 0.00324916 -0.00487399 -0.00092486 0
LR_13[cache_size=0.2,treshold=0.5] 0.00124968 -0.00324933 -0.000624897 -0.000124961
LR_13[cache_size=0.2,treshold=0.6] 0.00174946 -0.00262446 -0.000524918 -0.000374883
LR_13[cache_size=0.2,treshold=0.7] 0.00087473 -0.000249948 0.000324899 0.000374883
LR_13[cache_size=0.2,treshold=0.8] 0 0 0 0
LR_13[cache_size=0.2,treshold=0.9] 0 0 0 0
LR_14[cache_size=0.2,treshold=0.3] 0.00324916 -0.00487399 -0.00092486 0
LR_14[cache_size=0.2,treshold=0.5] 0.00124968 -0.00324933 -0.00064989 -0.000124961
LR_14[cache_size=0.2,treshold=0.6] 0.00174946 -0.00262446 -0.000399954 0
LR_14[cache_size=0.2,treshold=0.7] 0.000749805 -0.000374918 0.000249918 0.000374883
LR_14[cache_size=0.2,treshold=0.8] 0 0 0 0
LR_14[cache_size=0.2,treshold=0.9] 0 0 0 0
LR_15[cache_size=0.2,treshold=0.3] 0.00324916 -0.00487399 -0.000874876 0.000124961
LR_15[cache_size=0.2,treshold=0.5] 0.00137464 -0.0033743 -0.000699878 -0.000249922
LR_15[cache_size=0.2,treshold=0.6] 0.0016245 -0.00262446 -0.000449938 -0.000124961
LR_15[cache_size=0.2,treshold=0.7] 0.000874773 -0.000374918 0.000174943 0
LR_15[cache_size=0.2,treshold=0.8] 0 0 0 0
LR_15[cache_size=0.2,treshold=0.9] 0 0 0 0
LR_7[cache_size=0.2,treshold=0.3] 0.00374903 -0.00512394 -0.000899861 0
LR_7[cache_size=0.2,treshold=0.5] 0.00174955 -0.0033743 -0.000449947 -0.000374883
LR_7[cache_size=0.2,treshold=0.6] 0.00187442 -0.00212456 -0.000274984 0.000124961
LR_7[cache_size=0.2,treshold=0.7] 0.0016245 -0.00149969 0.000174909 0.000124968
LR_7[cache_size=0.2,treshold=0.8] 0 0 0 0
LR_7[cache_size=0.2,treshold=0.9] 0 0 0 0
LR_8[cache_size=0.2,treshold=0.3] 0.00362406 -0.00512394 -0.000899862 0.000249923
LR_8[cache_size=0.2,treshold=0.5] 0.00187451 -0.0033743 -0.000449946 -0.000249922
LR_8[cache_size=0.2,treshold=0.6] 0.00174946 -0.00224954 -0.000349965 0.000124961
LR_8[cache_size=0.2,treshold=0.7] 0.00124961 -0.00137472 0.000199907 0.000249935
LR_8[cache_size=0.2,treshold=0.8] 0 0 0 0
LR_8[cache_size=0.2,treshold=0.9] 0 0 0 0
LR_9[cache_size=0.2,treshold=0.3] 0.00362406 -0.00512394 -0.000949849 0.000124961
LR_9[cache_size=0.2,treshold=0.5] 0.00199948 -0.0033743 -0.00039996 -0.000249922
LR_9[cache_size=0.2,treshold=0.6] 0.00174946 -0.00224954 -0.00032497 0.000124961
LR_9[cache_size=0.2,treshold=0.7] 0.00112465 -0.00137472 0.000174917 0.000249935
LR_9[cache_size=0.2,treshold=0.8] 0 0 0 0
LR_9[cache_size=0.2,treshold=0.9] 0 0 0 0
LR_10[cache_size=0.4,treshold=0.3] 0.0071554 -0.000665599 0.00256262 0.00199709
LR_10[cache_size=0.4,treshold=0.5] 0.00532482 0 0.00203006 0.000831999
LR_10[cache_size=0.4,treshold=0.6] 0.00632323 -0.00282888 0.00189691 0.0013312
LR_10[cache_size=0.4,treshold=0.7] 0.00482562 -0.00183031 0.000698878 -0.000499272
LR_10[cache_size=0.4,treshold=0.8] 0.000166405 -0.000166424 -2.16048e-09 0
LR_10[cache_size=0.4,treshold=0.9] 0.000166401 -0.000166405 -6.65592e-05 -0.000166392
LR_11[cache_size=0.4,treshold=0.3] 0.00832023 -0.0004992 0.00279559 0.00216351
LR_11[cache_size=0.4,treshold=0.5] 0.00515842 -0.000166424 0.00186365 0.0004992
LR_11[cache_size=0.4,treshold=0.6] 0.00648963 -0.00332809 0.00178043 0.001664
LR_11[cache_size=0.4,treshold=0.7] 0.00565762 -0.00183066 0.000765402 -0.00099839
LR_11[cache_size=0.4,treshold=0.8] 0 -0.0001664 -6.65584e-05 0
LR_11[cache_size=0.4,treshold=0.9] 0 -0.000166392 -3.32784e-05 0
LR_12[cache_size=0.4,treshold=0.3] 0.00782102 -0.0013312 0.00252935 0.00216351
LR_12[cache_size=0.4,treshold=0.5] 0.00515842 -0.000166424 0.00189693 0.000665599
LR_12[cache_size=0.4,treshold=0.6] 0.00665603 -0.00316169 0.00183036 0.0013312
LR_12[cache_size=0.4,treshold=0.7] 0.00549122 -0.00232994 0.000632267 -0.000499214
LR_12[cache_size=0.4,treshold=0.8] 0 -0.0001664 -6.65584e-05 0
LR_12[cache_size=0.4,treshold=0.9] 0 -0.000166392 -3.32784e-05 0
LR_13[cache_size=0.4,treshold=0.3] 0.0063229 -0.0003328 0.00262909 0.00149761
LR_13[cache_size=0.4,treshold=0.5] 0.00482562 -0.002496 0.00159748 0.00116474
LR_13[cache_size=0.4,treshold=0.6] 0.00582402 -0.00199685 0.00206336 0.00166424
LR_13[cache_size=0.4,treshold=0.7] 0.00482562 -0.00282888 -0.000232996 -0.00149782
LR_13[cache_size=0.4,treshold=0.8] 0.000166401 -0.0001664 -3.32783e-05 0
LR_13[cache_size=0.4,treshold=0.9] 0.000166401 -0.000166392 1.71664e-09 0
LR_14[cache_size=0.4,treshold=0.3] 0.0063229 -0.0003328 0.00266237 0.00166401
LR_14[cache_size=0.4,treshold=0.5] 0.00482562 -0.0026624 0.0015642 0.00116474
LR_14[cache_size=0.4,treshold=0.6] 0.00599043 -0.00183045 0.0021632 0.00166424
LR_14[cache_size=0.4,treshold=0.7] 0.00499202 -0.00249607 -3.33202e-05 -0.00166424
LR_14[cache_size=0.4,treshold=0.8] 0.000166401 0 3.32801e-05 0
LR_14[cache_size=0.4,treshold=0.9] 0.000166401 -0.000166392 1.71664e-09 0
LR_15[cache_size=0.4,treshold=0.3] 0.00665568 -0.0004992 0.0027955 0.00166401
LR_15[cache_size=0.4,treshold=0.5] 0.00482562 -0.002496 0.00163076 0.00133114
LR_15[cache_size=0.4,treshold=0.6] 0.00582402 -0.00183045 0.00203009 0.00183066
LR_15[cache_size=0.4,treshold=0.7] 0.00449282 -0.00232966 -2.05505e-08 -0.000998544
LR_15[cache_size=0.4,treshold=0.8] 0.000166401 -0.000166392 1.71664e-09 0
LR_15[cache_size=0.4,treshold=0.9] 0.000166401 -0.000166392 1.71664e-09 0
LR_7[cache_size=0.4,treshold=0.3] 0.00815321 -0.00116497 0.00292857 0.000665599
LR_7[cache_size=0.4,treshold=0.5] 0.00482562 -0.0031616 0.00183046 0.00149782
LR_7[cache_size=0.4,treshold=0.6] 0.00615683 -0.00183045 0.00222974 0.00133139
LR_7[cache_size=0.4,treshold=0.7] 0.0004992 -0.000332809 6.65599e-05 0
LR_7[cache_size=0.4,treshold=0.8] 0.000332801 -0.000166405 9.41326e-10 0
LR_7[cache_size=0.4,treshold=0.9] 0.000332801 -0.000166405 3.32809e-05 0
LR_8[cache_size=0.4,treshold=0.3] 0.00865239 -0.00133139 0.00309496 0.00149761
LR_8[cache_size=0.4,treshold=0.5] 0.00499214 -0.003328 0.00186373 0.00166392
LR_8[cache_size=0.4,treshold=0.6] 0.00615683 -0.00149764 0.00246271 0.00149782
LR_8[cache_size=0.4,treshold=0.7] 0.0003328 -0.000166405 6.09054e-10 0
LR_8[cache_size=0.4,treshold=0.8] 0 0 0 0
LR_8[cache_size=0.4,treshold=0.9] 0 0 0 0
LR_9[cache_size=0.4,treshold=0.3] 0.00865239 -0.00133139 0.00306168 0.0011648
LR_9[cache_size=0.4,treshold=0.5] 0.00515854 -0.003328 0.00183044 0.00166392
LR_9[cache_size=0.4,treshold=0.6] 0.00615683 -0.00166405 0.00242942 0.00116497
LR_9[cache_size=0.4,treshold=0.7] 0.0003328 -0.000166424 -3.32842e-05 -0.000166392
LR_9[cache_size=0.4,treshold=0.8] 0 0 0 0
LR_9[cache_size=0.4,treshold=0.9] 0 0 0 0
Offline Clock 1st iteration 0 0 0 0
Offline Clock 2nd iteration 9.81851 0.0001001 2.73143 0.859981
Zipf Optimal Distribution 0.00682239 -0.00499176 0.000561115 0.000101012

Model Summaries Plot

Miss Ratio Reduced (%)

Promotion Reduced (%)

Promotion vs Miss Ratio

Cache Size All

Cache Size 0.001

Cache Size 0.01

Cache Size 0.1

Cache Size 0.2

Cache Size 0.4

Model Classification Report

LR_10_0.001

              precision    recall  f1-score   support

           0       0.02      0.57      0.04      1026
           1       1.00      0.94      0.97    499456

    accuracy                           0.94    500482
   macro avg       0.51      0.76      0.50    500482
weighted avg       1.00      0.94      0.97    500482

Accuracy: 0.9369647659656092
              precision    recall  f1-score   support

           0       0.02      0.57      0.04      1026
           1       1.00      0.94      0.97    499456

    accuracy                           0.94    500482
   macro avg       0.51      0.76      0.50    500482
weighted avg       1.00      0.94      0.97    500482

Accuracy: 0.9369647659656092

LR_10_0.01

              precision    recall  f1-score   support

           0       0.19      0.52      0.28     98473
           1       0.99      0.96      0.97   4925407

    accuracy                           0.95   5023880
   macro avg       0.59      0.74      0.63   5023880
weighted avg       0.97      0.95      0.96   5023880

Accuracy: 0.947614194606559
              precision    recall  f1-score   support

           0       0.19      0.52      0.28     98473
           1       0.99      0.96      0.97   4925407

    accuracy                           0.95   5023880
   macro avg       0.59      0.74      0.63   5023880
weighted avg       0.97      0.95      0.96   5023880

Accuracy: 0.947614194606559

LR_10_0.1

              precision    recall  f1-score   support

           0       0.41      0.57      0.48   8019514
           1       0.91      0.85      0.88  42910358

    accuracy                           0.80  50929872
   macro avg       0.66      0.71      0.68  50929872
weighted avg       0.83      0.80      0.81  50929872

Accuracy: 0.8026812240957527
              precision    recall  f1-score   support

           0       0.41      0.57      0.48   8019514
           1       0.91      0.85      0.88  42910358

    accuracy                           0.80  50929872
   macro avg       0.66      0.71      0.68  50929872
weighted avg       0.83      0.80      0.81  50929872

Accuracy: 0.8026812240957527

LR_10_0.2

              precision    recall  f1-score   support

           0       0.55      0.59      0.57  25620627
           1       0.85      0.83      0.84  73187446

    accuracy                           0.77  98808073
   macro avg       0.70      0.71      0.70  98808073
weighted avg       0.77      0.77      0.77  98808073

Accuracy: 0.7659223351112211
              precision    recall  f1-score   support

           0       0.55      0.59      0.57  25620627
           1       0.85      0.83      0.84  73187446

    accuracy                           0.77  98808073
   macro avg       0.70      0.71      0.70  98808073
weighted avg       0.77      0.77      0.77  98808073

Accuracy: 0.7659223351112211

LR_10_0.4

              precision    recall  f1-score   support

           0       0.62      0.68      0.65  66028440
           1       0.78      0.73      0.75 103663142

    accuracy                           0.71 169691582
   macro avg       0.70      0.71      0.70 169691582
weighted avg       0.72      0.71      0.71 169691582

Accuracy: 0.7110567924341704
              precision    recall  f1-score   support

           0       0.62      0.68      0.65  66028440
           1       0.78      0.73      0.75 103663142

    accuracy                           0.71 169691582
   macro avg       0.70      0.71      0.70 169691582
weighted avg       0.72      0.71      0.71 169691582

Accuracy: 0.7110567924341704

LR_10_All

              precision    recall  f1-score   support

           0       0.40      0.70      0.50  99768080
           1       0.80      0.53      0.64 225185809

    accuracy                           0.58 324953889
   macro avg       0.60      0.61      0.57 324953889
weighted avg       0.67      0.58      0.60 324953889

Accuracy: 0.5798402800466254
              precision    recall  f1-score   support

           0       0.40      0.70      0.50  99768080
           1       0.80      0.53      0.64 225185809

    accuracy                           0.58 324953889
   macro avg       0.60      0.61      0.57 324953889
weighted avg       0.67      0.58      0.60 324953889

Accuracy: 0.5798402800466254

LR_11_0.001

              precision    recall  f1-score   support

           0       0.01      0.66      0.01      1026
           1       1.00      0.75      0.86    499456

    accuracy                           0.75    500482
   macro avg       0.50      0.71      0.43    500482
weighted avg       1.00      0.75      0.86    500482

Accuracy: 0.752214864870265
              precision    recall  f1-score   support

           0       0.01      0.66      0.01      1026
           1       1.00      0.75      0.86    499456

    accuracy                           0.75    500482
   macro avg       0.50      0.71      0.43    500482
weighted avg       1.00      0.75      0.86    500482

Accuracy: 0.752214864870265

LR_11_0.01

              precision    recall  f1-score   support

           0       0.06      0.59      0.11     98473
           1       0.99      0.81      0.89   4925407

    accuracy                           0.81   5023880
   macro avg       0.53      0.70      0.50   5023880
weighted avg       0.97      0.81      0.88   5023880

Accuracy: 0.8104256072995374
              precision    recall  f1-score   support

           0       0.06      0.59      0.11     98473
           1       0.99      0.81      0.89   4925407

    accuracy                           0.81   5023880
   macro avg       0.53      0.70      0.50   5023880
weighted avg       0.97      0.81      0.88   5023880

Accuracy: 0.8104256072995374

LR_11_0.1

              precision    recall  f1-score   support

           0       0.41      0.57      0.47   8019514
           1       0.91      0.84      0.88  42910358

    accuracy                           0.80  50929872
   macro avg       0.66      0.71      0.68  50929872
weighted avg       0.83      0.80      0.81  50929872

Accuracy: 0.8009982235965565
              precision    recall  f1-score   support

           0       0.41      0.57      0.47   8019514
           1       0.91      0.84      0.88  42910358

    accuracy                           0.80  50929872
   macro avg       0.66      0.71      0.68  50929872
weighted avg       0.83      0.80      0.81  50929872

Accuracy: 0.8009982235965565

LR_11_0.2

              precision    recall  f1-score   support

           0       0.55      0.59      0.57  25620627
           1       0.85      0.83      0.84  73187446

    accuracy                           0.77  98808073
   macro avg       0.70      0.71      0.70  98808073
weighted avg       0.77      0.77      0.77  98808073

Accuracy: 0.767724131205352
              precision    recall  f1-score   support

           0       0.55      0.59      0.57  25620627
           1       0.85      0.83      0.84  73187446

    accuracy                           0.77  98808073
   macro avg       0.70      0.71      0.70  98808073
weighted avg       0.77      0.77      0.77  98808073

Accuracy: 0.767724131205352

LR_11_0.4

              precision    recall  f1-score   support

           0       0.62      0.68      0.65  66028440
           1       0.78      0.73      0.75 103663142

    accuracy                           0.71 169691582
   macro avg       0.70      0.71      0.70 169691582
weighted avg       0.72      0.71      0.71 169691582

Accuracy: 0.7109879911426602
              precision    recall  f1-score   support

           0       0.62      0.68      0.65  66028440
           1       0.78      0.73      0.75 103663142

    accuracy                           0.71 169691582
   macro avg       0.70      0.71      0.70 169691582
weighted avg       0.72      0.71      0.71 169691582

Accuracy: 0.7109998774128937

LR_11_All

              precision    recall  f1-score   support

           0       0.39      0.70      0.50  99768080
           1       0.80      0.53      0.63 225185809

    accuracy                           0.58 324953889
   macro avg       0.60      0.61      0.57 324953889
weighted avg       0.67      0.58      0.59 324953889

Accuracy: 0.5788021666052441
              precision    recall  f1-score   support

           0       0.39      0.70      0.50  99768080
           1       0.80      0.53      0.63 225185809

    accuracy                           0.58 324953889
   macro avg       0.60      0.61      0.57 324953889
weighted avg       0.67      0.58      0.59 324953889

Accuracy: 0.5788021666052441

LR_12_0.001

              precision    recall  f1-score   support

           0       0.01      0.61      0.02      1026
           1       1.00      0.85      0.92    499456

    accuracy                           0.85    500482
   macro avg       0.50      0.73      0.47    500482
weighted avg       1.00      0.85      0.92    500482

Accuracy: 0.8518348312227013
              precision    recall  f1-score   support

           0       0.01      0.61      0.02      1026
           1       1.00      0.85      0.92    499456

    accuracy                           0.85    500482
   macro avg       0.50      0.73      0.47    500482
weighted avg       1.00      0.85      0.92    500482

Accuracy: 0.8518348312227013

LR_12_0.01

              precision    recall  f1-score   support

           0       0.07      0.57      0.13     98473
           1       0.99      0.85      0.92   4925407

    accuracy                           0.85   5023880
   macro avg       0.53      0.71      0.52   5023880
weighted avg       0.97      0.85      0.90   5023880

Accuracy: 0.84876191310302
              precision    recall  f1-score   support

           0       0.07      0.57      0.13     98473
           1       0.99      0.85      0.92   4925407

    accuracy                           0.85   5023880
   macro avg       0.53      0.71      0.52   5023880
weighted avg       0.97      0.85      0.90   5023880

Accuracy: 0.84876191310302

LR_12_0.1

              precision    recall  f1-score   support

           0       0.41      0.57      0.48   8019514
           1       0.91      0.85      0.88  42910358

    accuracy                           0.80  50929872
   macro avg       0.66      0.71      0.68  50929872
weighted avg       0.83      0.80      0.82  50929872

Accuracy: 0.8031211034655653
              precision    recall  f1-score   support

           0       0.41      0.57      0.48   8019514
           1       0.91      0.85      0.88  42910358

    accuracy                           0.80  50929872
   macro avg       0.66      0.71      0.68  50929872
weighted avg       0.83      0.80      0.82  50929872

Accuracy: 0.8031211034655653

LR_12_0.2

              precision    recall  f1-score   support

           0       0.55      0.58      0.57  25620627
           1       0.85      0.83      0.84  73187446

    accuracy                           0.77  98808073
   macro avg       0.70      0.71      0.71  98808073
weighted avg       0.77      0.77      0.77  98808073

Accuracy: 0.7696034412086956
              precision    recall  f1-score   support

           0       0.55      0.58      0.57  25620627
           1       0.85      0.83      0.84  73187446

    accuracy                           0.77  98808073
   macro avg       0.70      0.71      0.71  98808073
weighted avg       0.77      0.77      0.77  98808073

Accuracy: 0.7696034412086956

LR_12_0.4

              precision    recall  f1-score   support

           0       0.62      0.68      0.65  66028440
           1       0.78      0.73      0.75 103663142

    accuracy                           0.71 169691582
   macro avg       0.70      0.71      0.70 169691582
weighted avg       0.72      0.71      0.71 169691582

Accuracy: 0.7110399618998189
              precision    recall  f1-score   support

           0       0.62      0.68      0.65  66028440
           1       0.78      0.73      0.75 103663142

    accuracy                           0.71 169691582
   macro avg       0.70      0.71      0.70 169691582
weighted avg       0.72      0.71      0.71 169691582

Accuracy: 0.7110399618998189

LR_12_All

              precision    recall  f1-score   support

           0       0.39      0.70      0.50  99768080
           1       0.80      0.53      0.63 225185809

    accuracy                           0.58 324953889
   macro avg       0.60      0.61      0.57 324953889
weighted avg       0.67      0.58      0.59 324953889

Accuracy: 0.5785499215859515
              precision    recall  f1-score   support

           0       0.39      0.70      0.50  99768080
           1       0.80      0.53      0.63 225185809

    accuracy                           0.58 324953889
   macro avg       0.60      0.61      0.57 324953889
weighted avg       0.67      0.58      0.59 324953889

Accuracy: 0.5785499215859515

LR_13_0.001

              precision    recall  f1-score   support

           0       0.02      0.57      0.04      1026
           1       1.00      0.94      0.97    499456

    accuracy                           0.94    500482
   macro avg       0.51      0.76      0.50    500482
weighted avg       1.00      0.94      0.97    500482

Accuracy: 0.9365531627511079
              precision    recall  f1-score   support

           0       0.02      0.57      0.04      1026
           1       1.00      0.94      0.97    499456

    accuracy                           0.94    500482
   macro avg       0.51      0.76      0.50    500482
weighted avg       1.00      0.94      0.97    500482

Accuracy: 0.9365531627511079

LR_13_0.01

              precision    recall  f1-score   support

           0       0.19      0.52      0.28     98473
           1       0.99      0.96      0.97   4925407

    accuracy                           0.95   5023880
   macro avg       0.59      0.74      0.63   5023880
weighted avg       0.97      0.95      0.96   5023880

Accuracy: 0.9475303948342715
              precision    recall  f1-score   support

           0       0.19      0.52      0.28     98473
           1       0.99      0.96      0.97   4925407

    accuracy                           0.95   5023880
   macro avg       0.59      0.74      0.63   5023880
weighted avg       0.97      0.95      0.96   5023880

Accuracy: 0.9475303948342715

LR_13_0.1

              precision    recall  f1-score   support

           0       0.42      0.56      0.48   8019514
           1       0.91      0.86      0.88  42910358

    accuracy                           0.81  50929872
   macro avg       0.67      0.71      0.68  50929872
weighted avg       0.84      0.81      0.82  50929872

Accuracy: 0.8108006829469353
              precision    recall  f1-score   support

           0       0.42      0.56      0.48   8019514
           1       0.91      0.86      0.88  42910358

    accuracy                           0.81  50929872
   macro avg       0.67      0.71      0.68  50929872
weighted avg       0.84      0.81      0.82  50929872

Accuracy: 0.8108006829469353

LR_13_0.2

              precision    recall  f1-score   support

           0       0.53      0.60      0.56  25620627
           1       0.85      0.81      0.83  73187446

    accuracy                           0.76  98808073
   macro avg       0.69      0.71      0.70  98808073
weighted avg       0.77      0.76      0.76  98808073

Accuracy: 0.7579026260334011
              precision    recall  f1-score   support

           0       0.53      0.60      0.56  25620627
           1       0.85      0.81      0.83  73187446

    accuracy                           0.76  98808073
   macro avg       0.69      0.71      0.70  98808073
weighted avg       0.77      0.76      0.76  98808073

Accuracy: 0.7579026260334011

LR_13_0.4

              precision    recall  f1-score   support

           0       0.65      0.65      0.65  66028440
           1       0.78      0.78      0.78 103663142

    accuracy                           0.73 169691582
   macro avg       0.71      0.71      0.71 169691582
weighted avg       0.73      0.73      0.73 169691582

Accuracy: 0.7285107696149594
              precision    recall  f1-score   support

           0       0.65      0.65      0.65  66028440
           1       0.78      0.78      0.78 103663142

    accuracy                           0.73 169691582
   macro avg       0.71      0.71      0.71 169691582
weighted avg       0.73      0.73      0.73 169691582

Accuracy: 0.7285107696149594

LR_13_All

              precision    recall  f1-score   support

           0       0.38      0.56      0.45  99768080
           1       0.75      0.60      0.67 225185809

    accuracy                           0.59 324953889
   macro avg       0.57      0.58      0.56 324953889
weighted avg       0.64      0.59      0.60 324953889

Accuracy: 0.5896379716815761
              precision    recall  f1-score   support

           0       0.38      0.56      0.45  99768080
           1       0.75      0.60      0.67 225185809

    accuracy                           0.59 324953889
   macro avg       0.57      0.58      0.56 324953889
weighted avg       0.64      0.59      0.60 324953889

Accuracy: 0.5896379716815761

LR_14_0.001

              precision    recall  f1-score   support

           0       0.01      0.66      0.01      1026
           1       1.00      0.75      0.86    499456

    accuracy                           0.75    500482
   macro avg       0.50      0.71      0.43    500482
weighted avg       1.00      0.75      0.86    500482

Accuracy: 0.752214864870265
              precision    recall  f1-score   support

           0       0.01      0.66      0.01      1026
           1       1.00      0.75      0.86    499456

    accuracy                           0.75    500482
   macro avg       0.50      0.71      0.43    500482
weighted avg       1.00      0.75      0.86    500482

Accuracy: 0.752214864870265

LR_14_0.01

              precision    recall  f1-score   support

           0       0.06      0.59      0.11     98473
           1       0.99      0.82      0.90   4925407

    accuracy                           0.82   5023880
   macro avg       0.53      0.71      0.51   5023880
weighted avg       0.97      0.82      0.88   5023880

Accuracy: 0.8189315827607347
              precision    recall  f1-score   support

           0       0.06      0.59      0.11     98473
           1       0.99      0.82      0.90   4925407

    accuracy                           0.82   5023880
   macro avg       0.53      0.71      0.51   5023880
weighted avg       0.97      0.82      0.88   5023880

Accuracy: 0.8189315827607347

LR_14_0.1

              precision    recall  f1-score   support

           0       0.40      0.57      0.47   8019514
           1       0.91      0.84      0.88  42910358

    accuracy                           0.80  50929872
   macro avg       0.66      0.71      0.67  50929872
weighted avg       0.83      0.80      0.81  50929872

Accuracy: 0.7984757157842455
              precision    recall  f1-score   support

           0       0.40      0.57      0.47   8019514
           1       0.91      0.84      0.88  42910358

    accuracy                           0.80  50929872
   macro avg       0.66      0.71      0.67  50929872
weighted avg       0.83      0.80      0.81  50929872

Accuracy: 0.7984757157842455

LR_14_0.2

              precision    recall  f1-score   support

           0       0.53      0.60      0.56  25620627
           1       0.85      0.81      0.83  73187446

    accuracy                           0.76  98808073
   macro avg       0.69      0.70      0.70  98808073
weighted avg       0.77      0.76      0.76  98808073

Accuracy: 0.7577006081274351
              precision    recall  f1-score   support

           0       0.53      0.60      0.56  25620627
           1       0.85      0.81      0.83  73187446

    accuracy                           0.76  98808073
   macro avg       0.69      0.70      0.70  98808073
weighted avg       0.77      0.76      0.76  98808073

Accuracy: 0.7577006081274351

LR_14_0.4

              precision    recall  f1-score   support

           0       0.65      0.65      0.65  66028440
           1       0.78      0.78      0.78 103663142

    accuracy                           0.73 169691582
   macro avg       0.71      0.71      0.71 169691582
weighted avg       0.73      0.73      0.73 169691582

Accuracy: 0.7285412602258609
              precision    recall  f1-score   support

           0       0.65      0.65      0.65  66028440
           1       0.78      0.78      0.78 103663142

    accuracy                           0.73 169691582
   macro avg       0.71      0.71      0.71 169691582
weighted avg       0.73      0.73      0.73 169691582

Accuracy: 0.7285412602258609

LR_14_All

              precision    recall  f1-score   support

           0       0.38      0.56      0.45  99768080
           1       0.75      0.60      0.67 225185809

    accuracy                           0.59 324953889
   macro avg       0.57      0.58      0.56 324953889
weighted avg       0.64      0.59      0.60 324953889

Accuracy: 0.5899010643937854
              precision    recall  f1-score   support

           0       0.38      0.56      0.45  99768080
           1       0.75      0.60      0.67 225185809

    accuracy                           0.59 324953889
   macro avg       0.57      0.58      0.56 324953889
weighted avg       0.64      0.59      0.60 324953889

Accuracy: 0.5899010643937854

LR_15_0.001

              precision    recall  f1-score   support

           0       0.01      0.61      0.02      1026
           1       1.00      0.85      0.92    499456

    accuracy                           0.85    500482
   macro avg       0.50      0.73      0.47    500482
weighted avg       1.00      0.85      0.92    500482

Accuracy: 0.8517648986377132
              precision    recall  f1-score   support

           0       0.01      0.61      0.02      1026
           1       1.00      0.85      0.92    499456

    accuracy                           0.85    500482
   macro avg       0.50      0.73      0.47    500482
weighted avg       1.00      0.85      0.92    500482

Accuracy: 0.8517648986377132

LR_15_0.01

              precision    recall  f1-score   support

           0       0.08      0.57      0.13     98473
           1       0.99      0.86      0.92   4925407

    accuracy                           0.86   5023880
   macro avg       0.53      0.72      0.53   5023880
weighted avg       0.97      0.86      0.91   5023880

Accuracy: 0.8553002858348527
              precision    recall  f1-score   support

           0       0.08      0.57      0.13     98473
           1       0.99      0.86      0.92   4925407

    accuracy                           0.86   5023880
   macro avg       0.53      0.72      0.53   5023880
weighted avg       0.97      0.86      0.91   5023880

Accuracy: 0.8553002858348527

LR_15_0.1

              precision    recall  f1-score   support

           0       0.40      0.57      0.47   8019514
           1       0.91      0.84      0.88  42910358

    accuracy                           0.80  50929872
   macro avg       0.66      0.71      0.67  50929872
weighted avg       0.83      0.80      0.81  50929872

Accuracy: 0.7984756765145611
              precision    recall  f1-score   support

           0       0.40      0.57      0.47   8019514
           1       0.91      0.84      0.88  42910358

    accuracy                           0.80  50929872
   macro avg       0.66      0.71      0.67  50929872
weighted avg       0.83      0.80      0.81  50929872

Accuracy: 0.7984756765145611

LR_15_0.2

              precision    recall  f1-score   support

           0       0.53      0.60      0.56  25620627
           1       0.85      0.81      0.83  73187446

    accuracy                           0.76  98808073
   macro avg       0.69      0.71      0.70  98808073
weighted avg       0.77      0.76      0.76  98808073

Accuracy: 0.7579156108023684
              precision    recall  f1-score   support

           0       0.53      0.60      0.56  25620627
           1       0.85      0.81      0.83  73187446

    accuracy                           0.76  98808073
   macro avg       0.69      0.71      0.70  98808073
weighted avg       0.77      0.76      0.76  98808073

Accuracy: 0.7579156108023684

LR_15_0.4

              precision    recall  f1-score   support

           0       0.65      0.65      0.65  66028440
           1       0.78      0.78      0.78 103663142

    accuracy                           0.73 169691582
   macro avg       0.71      0.71      0.71 169691582
weighted avg       0.73      0.73      0.73 169691582

Accuracy: 0.7285153249381575
              precision    recall  f1-score   support

           0       0.65      0.65      0.65  66028440
           1       0.78      0.78      0.78 103663142

    accuracy                           0.73 169691582
   macro avg       0.71      0.71      0.71 169691582
weighted avg       0.73      0.73      0.73 169691582

Accuracy: 0.7285153249381575

LR_15_All

              precision    recall  f1-score   support

           0       0.38      0.56      0.45  99768080
           1       0.75      0.61      0.67 225185809

    accuracy                           0.59 324953889
   macro avg       0.57      0.58      0.56 324953889
weighted avg       0.64      0.59      0.61 324953889

Accuracy: 0.5901402275570242
              precision    recall  f1-score   support

           0       0.38      0.56      0.45  99768080
           1       0.75      0.61      0.67 225185809

    accuracy                           0.59 324953889
   macro avg       0.57      0.58      0.56 324953889
weighted avg       0.64      0.59      0.61 324953889

Accuracy: 0.5901402275570242

LR_7_0.001

              precision    recall  f1-score   support

           0       0.02      0.57      0.04      1026
           1       1.00      0.94      0.97    499456

    accuracy                           0.94    500482
   macro avg       0.51      0.76      0.50    500482
weighted avg       1.00      0.94      0.97    500482

Accuracy: 0.9368788487897667
              precision    recall  f1-score   support

           0       0.02      0.57      0.04      1026
           1       1.00      0.94      0.97    499456

    accuracy                           0.94    500482
   macro avg       0.51      0.76      0.50    500482
weighted avg       1.00      0.94      0.97    500482

Accuracy: 0.9368788487897667

LR_7_0.01

              precision    recall  f1-score   support

           0       0.19      0.52      0.28     98473
           1       0.99      0.96      0.97   4925407

    accuracy                           0.95   5023880
   macro avg       0.59      0.74      0.63   5023880
weighted avg       0.97      0.95      0.96   5023880

Accuracy: 0.9476126022118363
              precision    recall  f1-score   support

           0       0.19      0.52      0.28     98473
           1       0.99      0.96      0.97   4925407

    accuracy                           0.95   5023880
   macro avg       0.59      0.74      0.63   5023880
weighted avg       0.97      0.95      0.96   5023880

Accuracy: 0.9476126022118363

LR_7_0.1

              precision    recall  f1-score   support

           0       0.38      0.58      0.46   8019514
           1       0.91      0.83      0.87  42910358

    accuracy                           0.79  50929872
   macro avg       0.65      0.70      0.66  50929872
weighted avg       0.83      0.79      0.80  50929872

Accuracy: 0.7869018009705581
              precision    recall  f1-score   support

           0       0.38      0.58      0.46   8019514
           1       0.91      0.83      0.87  42910358

    accuracy                           0.79  50929872
   macro avg       0.65      0.70      0.66  50929872
weighted avg       0.83      0.79      0.80  50929872

Accuracy: 0.7869018009705581

LR_7_0.2

              precision    recall  f1-score   support

           0       0.50      0.61      0.55  25620627
           1       0.85      0.79      0.82  73187446

    accuracy                           0.74  98808073
   macro avg       0.68      0.70      0.69  98808073
weighted avg       0.76      0.74      0.75  98808073

Accuracy: 0.742507527699685
              precision    recall  f1-score   support

           0       0.50      0.61      0.55  25620627
           1       0.85      0.79      0.82  73187446

    accuracy                           0.74  98808073
   macro avg       0.68      0.70      0.69  98808073
weighted avg       0.76      0.74      0.75  98808073

Accuracy: 0.742507527699685

LR_7_0.4

              precision    recall  f1-score   support

           0       0.67      0.64      0.65  66028440
           1       0.78      0.80      0.79 103663142

    accuracy                           0.74 169691582
   macro avg       0.72      0.72      0.72 169691582
weighted avg       0.73      0.74      0.73 169691582

Accuracy: 0.7354215956334239
              precision    recall  f1-score   support

           0       0.67      0.64      0.65  66028440
           1       0.78      0.80      0.79 103663142

    accuracy                           0.74 169691582
   macro avg       0.72      0.72      0.72 169691582
weighted avg       0.73      0.74      0.73 169691582

Accuracy: 0.7354215956334239

LR_7_All

              precision    recall  f1-score   support

           0       0.44      0.58      0.50  99768080
           1       0.78      0.68      0.73 225185809

    accuracy                           0.65 324953889
   macro avg       0.61      0.63      0.62 324953889
weighted avg       0.68      0.65      0.66 324953889

Accuracy: 0.6482772452678663
              precision    recall  f1-score   support

           0       0.44      0.58      0.50  99768080
           1       0.78      0.68      0.73 225185809

    accuracy                           0.65 324953889
   macro avg       0.61      0.63      0.62 324953889
weighted avg       0.68      0.65      0.66 324953889

Accuracy: 0.6482772452678663

LR_8_0.001

              precision    recall  f1-score   support

           0       0.01      0.66      0.01      1026
           1       1.00      0.75      0.86    499456

    accuracy                           0.75    500482
   macro avg       0.50      0.71      0.43    500482
weighted avg       1.00      0.75      0.86    500482

Accuracy: 0.752214864870265
              precision    recall  f1-score   support

           0       0.01      0.66      0.01      1026
           1       1.00      0.75      0.86    499456

    accuracy                           0.75    500482
   macro avg       0.50      0.71      0.43    500482
weighted avg       1.00      0.75      0.86    500482

Accuracy: 0.752214864870265

LR_8_0.01

              precision    recall  f1-score   support

           0       0.06      0.60      0.11     98473
           1       0.99      0.81      0.89   4925407

    accuracy                           0.80   5023880
   macro avg       0.52      0.70      0.50   5023880
weighted avg       0.97      0.80      0.87   5023880

Accuracy: 0.8023917768736515
              precision    recall  f1-score   support

           0       0.06      0.60      0.11     98473
           1       0.99      0.81      0.89   4925407

    accuracy                           0.80   5023880
   macro avg       0.52      0.70      0.50   5023880
weighted avg       0.97      0.80      0.87   5023880

Accuracy: 0.8023917768736515

LR_8_0.1

              precision    recall  f1-score   support

           0       0.35      0.60      0.44   8019514
           1       0.91      0.79      0.85  42910358

    accuracy                           0.76  50929872
   macro avg       0.63      0.69      0.64  50929872
weighted avg       0.82      0.76      0.78  50929872

Accuracy: 0.7604401008508327
              precision    recall  f1-score   support

           0       0.35      0.60      0.44   8019514
           1       0.91      0.79      0.85  42910358

    accuracy                           0.76  50929872
   macro avg       0.63      0.69      0.64  50929872
weighted avg       0.82      0.76      0.78  50929872

Accuracy: 0.7604401008508327

LR_8_0.2

              precision    recall  f1-score   support

           0       0.50      0.61      0.55  25620627
           1       0.85      0.79      0.82  73187446

    accuracy                           0.74  98808073
   macro avg       0.68      0.70      0.69  98808073
weighted avg       0.76      0.74      0.75  98808073

Accuracy: 0.743415338137401
              precision    recall  f1-score   support

           0       0.50      0.61      0.55  25620627
           1       0.85      0.79      0.82  73187446

    accuracy                           0.74  98808073
   macro avg       0.68      0.70      0.69  98808073
weighted avg       0.76      0.74      0.75  98808073

Accuracy: 0.743415338137401

LR_8_0.4

              precision    recall  f1-score   support

           0       0.67      0.64      0.65  66028440
           1       0.78      0.80      0.79 103663142

    accuracy                           0.74 169691582
   macro avg       0.72      0.72      0.72 169691582
weighted avg       0.73      0.74      0.74 169691582

Accuracy: 0.7360847575809624
              precision    recall  f1-score   support

           0       0.67      0.64      0.65  66028440
           1       0.78      0.80      0.79 103663142

    accuracy                           0.74 169691582
   macro avg       0.72      0.72      0.72 169691582
weighted avg       0.73      0.74      0.74 169691582

Accuracy: 0.7360847575809624

LR_8_All

              precision    recall  f1-score   support

           0       0.44      0.58      0.50  99768080
           1       0.78      0.68      0.73 225185809

    accuracy                           0.65 324953889
   macro avg       0.61      0.63      0.62 324953889
weighted avg       0.68      0.65      0.66 324953889

Accuracy: 0.64812848877768
              precision    recall  f1-score   support

           0       0.44      0.58      0.50  99768080
           1       0.78      0.68      0.73 225185809

    accuracy                           0.65 324953889
   macro avg       0.61      0.63      0.62 324953889
weighted avg       0.68      0.65      0.66 324953889

Accuracy: 0.64812848877768

LR_9_0.001

              precision    recall  f1-score   support

           0       0.01      0.61      0.02      1026
           1       1.00      0.85      0.92    499456

    accuracy                           0.85    500482
   macro avg       0.50      0.73      0.47    500482
weighted avg       1.00      0.85      0.92    500482

Accuracy: 0.8512813647643671
              precision    recall  f1-score   support

           0       0.01      0.61      0.02      1026
           1       1.00      0.85      0.92    499456

    accuracy                           0.85    500482
   macro avg       0.50      0.73      0.47    500482
weighted avg       1.00      0.85      0.92    500482

Accuracy: 0.8512813647643671

LR_9_0.01

              precision    recall  f1-score   support

           0       0.07      0.58      0.13     98473
           1       0.99      0.85      0.91   4925407

    accuracy                           0.84   5023880
   macro avg       0.53      0.71      0.52   5023880
weighted avg       0.97      0.84      0.90   5023880

Accuracy: 0.841862265818451
              precision    recall  f1-score   support

           0       0.07      0.58      0.13     98473
           1       0.99      0.85      0.91   4925407

    accuracy                           0.84   5023880
   macro avg       0.53      0.71      0.52   5023880
weighted avg       0.97      0.84      0.90   5023880

Accuracy: 0.841862265818451

LR_9_0.1

              precision    recall  f1-score   support

           0       0.35      0.60      0.44   8019514
           1       0.91      0.79      0.85  42910358

    accuracy                           0.76  50929872
   macro avg       0.63      0.69      0.64  50929872
weighted avg       0.82      0.76      0.78  50929872

Accuracy: 0.7617056449700089
              precision    recall  f1-score   support

           0       0.35      0.60      0.44   8019514
           1       0.91      0.79      0.85  42910358

    accuracy                           0.76  50929872
   macro avg       0.63      0.69      0.64  50929872
weighted avg       0.82      0.76      0.78  50929872

Accuracy: 0.7617056449700089

LR_9_0.2

              precision    recall  f1-score   support

           0       0.50      0.61      0.55  25620627
           1       0.85      0.79      0.82  73187446

    accuracy                           0.74  98808073
   macro avg       0.68      0.70      0.69  98808073
weighted avg       0.76      0.74      0.75  98808073

Accuracy: 0.743784457774012
              precision    recall  f1-score   support

           0       0.50      0.61      0.55  25620627
           1       0.85      0.79      0.82  73187446

    accuracy                           0.74  98808073
   macro avg       0.68      0.70      0.69  98808073
weighted avg       0.76      0.74      0.75  98808073

Accuracy: 0.743784457774012

LR_9_0.4

              precision    recall  f1-score   support

           0       0.67      0.64      0.65  66028440
           1       0.78      0.80      0.79 103663142

    accuracy                           0.74 169691582
   macro avg       0.72      0.72      0.72 169691582
weighted avg       0.73      0.74      0.74 169691582

Accuracy: 0.7361713499730352
              precision    recall  f1-score   support

           0       0.67      0.64      0.65  66028440
           1       0.78      0.80      0.79 103663142

    accuracy                           0.74 169691582
   macro avg       0.72      0.72      0.72 169691582
weighted avg       0.73      0.74      0.74 169691582

Accuracy: 0.7361713499730352

LR_9_All

              precision    recall  f1-score   support

           0       0.44      0.58      0.50  99768080
           1       0.78      0.68      0.73 225185809

    accuracy                           0.65 324953889
   macro avg       0.61      0.63      0.62 324953889
weighted avg       0.68      0.65      0.66 324953889

Accuracy: 0.6483561333835891
              precision    recall  f1-score   support

           0       0.44      0.58      0.50  99768080
           1       0.78      0.68      0.73 225185809

    accuracy                           0.65 324953889
   macro avg       0.61      0.63      0.62 324953889
weighted avg       0.68      0.65      0.66 324953889

Accuracy: 0.6483561333835891

Model Metrics

True Positives

True Negatives

False Positives

False Negatives

Individual Workload Result

zipf_0_15

0.001

0.01

0.1

0.2

0.4

Ignore Obj Size

0.001

0.01

0.1

0.2

0.4

zipf_0_16

0.001

0.01

0.1

0.2

0.4

Ignore Obj Size

0.001

0.01

0.1

0.2

0.4

zipf_0_17

0.001

0.01

0.1

0.2

0.4

Ignore Obj Size

0.001

0.01

0.1

0.2

0.4

zipf_0_18

0.001

0.01

0.1

0.2

0.4

Ignore Obj Size

0.001

0.01

0.1

0.2

0.4

zipf_0_19

0.001

0.01

0.1

0.2

0.4

Ignore Obj Size

0.001

0.01

0.1

0.2

0.4